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Alibaba made Qwen 3.8 Max free on Qoder Desktop for 14 days it's their 2.4T parameter model. rivals Fable 5 on coding benchmarks. runs in a desktop IDE. what you get for $0: -2.4 trillion parameters -Qwen3.8-Max-Preview in a full agentic IDE -code completion, test generation, file editing -2-week... show more

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FREE CLAUDE FABLE 5 and almost nobody knows this trick Anthropic recently released their most capable model ever - the first Mythos-class model available to the public normally it's $10/$50 per million tokens but there's a hack: GitLab just added Fable 5 to Duo Agent Platform - across ALL tiers, including free trial the setup: 1/ register a GitLab account: 2/ start the free GitLab Duo trial 3/ Fable 5 is live through their AI Gateway 4/ done - Mythos-class model, $0 why Fable 5 is worth the hype: 1/ 80.3% SWE-Bench Pro - 11 points ahead of the next best model 2/ multi-DAY autonomous runs without losing the plot 3/ single-pass implementations of systems that took days of iteration 4/ Karpathy called it 'a major-version-bump-deserving step change' also free on Claude Pro/Max/Team until June 22 - after that it's usage credits you have a limited window to run the most capable public model on the planet for FREE

FREE CLAUDE FABLE 5 and almost nobody knows this trick Anthropic recently released their most capable model ever - the first Mythos-class model available to the public normally it's $10/$50 per million tokens but there's a hack: GitLab just added Fable 5 to Duo Agent Platform - across ALL tiers, including free trial the setup: 1/ register a GitLab account: 2/ start the free GitLab Duo trial 3/ Fable 5 is live through their AI Gateway 4/ done - Mythos-class model, $0 why Fable 5 is worth the hype: 1/ 80.3% SWE-Bench Pro - 11 points ahead of the next best model 2/ multi-DAY autonomous runs without losing the plot 3/ single-pass implementations of systems that took days of iteration 4/ Karpathy called it 'a major-version-bump-deserving step change' also free on Claude Pro/Max/Team until June 22 - after that it's usage credits you have a limited window to run the most capable public model on the planet for FREE

kaize

24,221 görüntüleme • 1 ay önce

FREE Fable 5, Opus 4.8, Sonnet 5, and GPT-5.6 in one IDE. Alibaba built it, 520 credits at signup - one Sonnet 5 message eats 4. It's called Accio. Web or Windows desktop, both free. Registration takes 30 seconds via Google or email. Inside: → Fable 5 for creative and long-context work. → Opus 4.6 through 4.8 - the full Anthropic frontier lineup. → Sonnet 5 for speed and reasoning at pennies per message. → GPT-5.5 for OpenAI native tasks. → Gemini 3.1 Pro and 3.5 Flash for multimodal. Real math: 520 credits divided by 4 = 130 Sonnet 5 messages in your first week. Cheaper models drop that even further. Anthropic charges $20/month for the same access with weekly limits. Custom MCP support built in. Profile > Settings > MCP. Every agent workflow you've built for Claude Desktop ports over instantly. Setup: → Go to accio(.)com → Sign up with Google → 520 credits land automatically → Pick your model and start firing prompts Bookmark this before Alibaba puts it behind a paywall.

Atenov int.

31,157 görüntüleme • 10 gün önce

this is f**king dangerous someone just figured out how to get fable 5 reasoning in opus 4.8 with one prompt you have less than 24 hours to set this up as this takes away 20% of your usage limit here is how: 1) Paste the prompt and ask it to "make an operating manual" 2) Create a New Claude Project and "Add this .md in Project instructions 3) Use Opus 4.8 High/Max and now you have Fable 5 reasoning at 1/5th the price save and bookmark it no matter what

this is f**king dangerous someone just figured out how to get fable 5 reasoning in opus 4.8 with one prompt you have less than 24 hours to set this up as this takes away 20% of your usage limit here is how: 1) Paste the prompt and ask it to "make an operating manual" 2) Create a New Claude Project and "Add this .md in Project instructions 3) Use Opus 4.8 High/Max and now you have Fable 5 reasoning at 1/5th the price save and bookmark it no matter what

Avid

944,814 görüntüleme • 19 gün önce

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.

Julian Goldie SEO

30,259 görüntüleme • 5 ay önce

Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.

Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.

Harman

41,179 görüntüleme • 17 gün önce

AMD'S NEW MINI PC RUNS CLAUDE CODE OFFLINE FOR $0/MONTH AND REPLACES $200 OPENAI + $200 CLAUDE CODE SUBSCRIPTIONS amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on a single piece of silicon with 128gb of unified memory the gmktec evo-x2 runs qwen3 coder 30b at 40 to 50 tokens per second and llama 3.3 70b at 20 to 25 tokens per second locally. on linux you get 110gb of usable vram out of 128gb setup takes 90 minutes. wipe windows for linux, install ollama with one command, pull the model, point claude code at localhost. same interface, same agent loop, nothing leaves your network a heavy ai user pays $200 for claude code max, $200 for chatgpt pro and $20 for cursor. that's $5,040 a year and the box pays itself off in 5 months after break-even every month is $420 that used to leave your account. three year math is roughly $13,000 not paid to ai companies plus zero rate limits on overnight agents bookmark this and read the article below

AMD'S NEW MINI PC RUNS CLAUDE CODE OFFLINE FOR $0/MONTH AND REPLACES $200 OPENAI + $200 CLAUDE CODE SUBSCRIPTIONS amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on a single piece of silicon with 128gb of unified memory the gmktec evo-x2 runs qwen3 coder 30b at 40 to 50 tokens per second and llama 3.3 70b at 20 to 25 tokens per second locally. on linux you get 110gb of usable vram out of 128gb setup takes 90 minutes. wipe windows for linux, install ollama with one command, pull the model, point claude code at localhost. same interface, same agent loop, nothing leaves your network a heavy ai user pays $200 for claude code max, $200 for chatgpt pro and $20 for cursor. that's $5,040 a year and the box pays itself off in 5 months after break-even every month is $420 that used to leave your account. three year math is roughly $13,000 not paid to ai companies plus zero rate limits on overnight agents bookmark this and read the article below

starmex

33,516 görüntüleme • 1 ay önce

$I just realized I've been scheduling my biggest AI jobs at the worst possible time, and it was costing me up to 80% more than it needed to. Qoder now runs Qwen3.7-Max and Qwen3.7-Plus with off-peak rates, which means the same models cost significantly less during the off-peak window. here's what changed: • Qwen3.7-Max: 0.5x → 0.1x (up to 80% off) • Qwen3.7-Plus: 0.1x → 0.04x (60% off) the model doesn't change. the reasoning doesn't change. the context length doesn't change. only the credit multiplier does. and the best part? the off-peak rates are applied automatically. no configuration needed. so instead of launching long refactors, migrations, agent runs, or large code generation whenever I think about them... I simply queue them during my off-peak window ( to local time) and let the same flagship Qwen model do the work for a fraction of the usual cost. that's probably the easiest productivity upgrade I've made this month. switch to Qwen3.7-Max or Qwen3.7-Plus in Qoder during your local off-peak hours and compare the credits before and after. search "Google Qoder" or download it here:$

I just realized I've been scheduling my biggest AI jobs at the worst possible time, and it was costing me up to 80% more than it needed to. Qoder now runs Qwen3.7-Max and Qwen3.7-Plus with off-peak rates, which means the same models cost significantly less during the off-peak window. here's what changed: • Qwen3.7-Max: 0.5x → 0.1x (up to 80% off) • Qwen3.7-Plus: 0.1x → 0.04x (60% off) the model doesn't change. the reasoning doesn't change. the context length doesn't change. only the credit multiplier does. and the best part? the off-peak rates are applied automatically. no configuration needed. so instead of launching long refactors, migrations, agent runs, or large code generation whenever I think about them... I simply queue them during my off-peak window ( to local time) and let the same flagship Qwen model do the work for a fraction of the usual cost. that's probably the easiest productivity upgrade I've made this month. switch to Qwen3.7-Max or Qwen3.7-Plus in Qoder during your local off-peak hours and compare the credits before and after. search "Google Qoder" or download it here:

marcus

24,620 görüntüleme • 22 gün önce

If you're someone that genuinely believes this, I'm sorry for you. 1) No functioning adult is out there prying at their lenses covers with a knife. 2) The lenses covers are glued on shut, he struggled to take it off when he poked it with a knife. They won't fall off if you use your phone normally. 3) before you bring up the 15 Pro bend test: phones are supposed to go in pockets, which are normally tight. If it can't handle a flex, that's the phone's problem, and he showed that. In no world will a lens cover suddenly fall.

If you're someone that genuinely believes this, I'm sorry for you. 1) No functioning adult is out there prying at their lenses covers with a knife. 2) The lenses covers are glued on shut, he struggled to take it off when he poked it with a knife. They won't fall off if you use your phone normally. 3) before you bring up the 15 Pro bend test: phones are supposed to go in pockets, which are normally tight. If it can't handle a flex, that's the phone's problem, and he showed that. In no world will a lens cover suddenly fall.

Amir

32,548 görüntüleme • 1 yıl önce

A few weeks ago the US government forced Claude Fable 5 offline. It's back. And before they switch it off again, this is your shot to point the most powerful AI on earth at something of your own. Take the 26-year-old in Toronto. His bot went dark the day Fable 5 got pulled. The day it came back, it woke up and started printing again - $568,000 profit and counting. His wallet: Here's the story. When the ban hit, Anthropic had to switch Fable 5 off for everyone. They called it a misunderstanding with the government. Whatever it was, every bot running on that model stopped cold. His was one of them. He didn't rebuild a thing. The loop just sat there, paused, for weeks. Here's what that loop actually does. It's not one prompt to an AI. It's an agentic loop: a team of agents running on repeat. One reads the market, one places the trade, one tries to prove it wrong before a cent moves. Then it goes again, around the clock, keeping what works and dropping what doesn't. Fable 5 is the brain running that team. The exact model the government decided was too powerful to leave on. Point it at Bitcoin's 5-minute markets and it barely misses. Most of its trades close green, and it runs itself. He checks it from his phone. The government could switch off the model. It couldn't switch off the idea. Now the model's back, and so is the money. Save this before next headline. You'll want it the day Fable 5 hits offline again.

A few weeks ago the US government forced Claude Fable 5 offline. It's back. And before they switch it off again, this is your shot to point the most powerful AI on earth at something of your own. Take the 26-year-old in Toronto. His bot went dark the day Fable 5 got pulled. The day it came back, it woke up and started printing again - $568,000 profit and counting. His wallet: Here's the story. When the ban hit, Anthropic had to switch Fable 5 off for everyone. They called it a misunderstanding with the government. Whatever it was, every bot running on that model stopped cold. His was one of them. He didn't rebuild a thing. The loop just sat there, paused, for weeks. Here's what that loop actually does. It's not one prompt to an AI. It's an agentic loop: a team of agents running on repeat. One reads the market, one places the trade, one tries to prove it wrong before a cent moves. Then it goes again, around the clock, keeping what works and dropping what doesn't. Fable 5 is the brain running that team. The exact model the government decided was too powerful to leave on. Point it at Bitcoin's 5-minute markets and it barely misses. Most of its trades close green, and it runs itself. He checks it from his phone. The government could switch off the model. It couldn't switch off the idea. Now the model's back, and so is the money. Save this before next headline. You'll want it the day Fable 5 hits offline again.

cvxv666

24,055 görüntüleme • 24 gün önce

no money for grok or midjourney? this tool is for you. there's a FREE tool created by an anon dev. open-source. runs locally. 117k stars on github. it generates: > images & video > 3d models > audio > 20+ models here's how to set it up in under 5 minutes: 1️⃣download ComfyUI Desktop go to and grab the desktop app for your system. windows 10+, mac (apple silicon), or linux. it installs like any normal app, it sets up python and every dependency for you in the background. no terminal, no config files. 2️⃣open it first launch, it spins up its own environment automatically. you just wait a few seconds and you're in. you'll land on a node canvas, that's the whole interface. 3️⃣load a starter workflow top menu → Workflow → Browse Templates → Image Generation. click it. this drops a ready-made setup onto your canvas so you don't build anything from scratch. 4️⃣grab a model comfyui ships empty on purpose, the model is the brain, and you pick it. in the template, the "Load Checkpoint" node has a Download button when no model is installed. click it. it pulls one in for you (a few GB, this is the only real wait). 5️⃣install ComfyUI Manager this is the one add-on you don't skip. it lets you install models, custom nodes, and updates with a click instead of the command line. grab it from github (link in comments). it's the difference between fighting comfyui and flying in it. one honest note: an NVIDIA gpu makes this fast, apple silicon works great too, and a weak machine still runs it just slower. that's the whole setup. you now own an image, video, and 3D studio that costs you nothing per month. save this. and the next time grok or midjourney asks for your card. you won't need it. disclaimer: comfyui itself is 100% free. so are the local models (sdxl, flux, wan 2.2, ltx-2). some premium models like seedance are pay-per-use api models, only if you want top-tier quality. the free local ones cover most of what you need. (github link in the comments) follow and turn on post notification for daily AI contents.

no money for grok or midjourney? this tool is for you. there's a FREE tool created by an anon dev. open-source. runs locally. 117k stars on github. it generates: > images & video > 3d models > audio > 20+ models here's how to set it up in under 5 minutes: 1️⃣download ComfyUI Desktop go to and grab the desktop app for your system. windows 10+, mac (apple silicon), or linux. it installs like any normal app, it sets up python and every dependency for you in the background. no terminal, no config files. 2️⃣open it first launch, it spins up its own environment automatically. you just wait a few seconds and you're in. you'll land on a node canvas, that's the whole interface. 3️⃣load a starter workflow top menu → Workflow → Browse Templates → Image Generation. click it. this drops a ready-made setup onto your canvas so you don't build anything from scratch. 4️⃣grab a model comfyui ships empty on purpose, the model is the brain, and you pick it. in the template, the "Load Checkpoint" node has a Download button when no model is installed. click it. it pulls one in for you (a few GB, this is the only real wait). 5️⃣install ComfyUI Manager this is the one add-on you don't skip. it lets you install models, custom nodes, and updates with a click instead of the command line. grab it from github (link in comments). it's the difference between fighting comfyui and flying in it. one honest note: an NVIDIA gpu makes this fast, apple silicon works great too, and a weak machine still runs it just slower. that's the whole setup. you now own an image, video, and 3D studio that costs you nothing per month. save this. and the next time grok or midjourney asks for your card. you won't need it. disclaimer: comfyui itself is 100% free. so are the local models (sdxl, flux, wan 2.2, ltx-2). some premium models like seedance are pay-per-use api models, only if you want top-tier quality. the free local ones cover most of what you need. (github link in the comments) follow and turn on post notification for daily AI contents.

m0h

14,542 görüntüleme • 1 ay önce

CLAUDE FABLE 5 IS BACK, BUT IS IT THE SAME POWER OR WAS IT QUIETLY TRIMMED Fable 5 is available again. Anthropic's most powerful model is back globally for every paid account When it first landed three weeks ago, the difference was obvious right away. It didn't just help, it carried the task to the finish: entire web projects, presentations, reports, analysis. People dropped their work on other models and simply waited for Fable And the wait happened because three days after launch the US hit the model with export controls. There was no clean way to cut off foreign nationals, so Anthropic shut access down for everyone Now the restrictions are lifted, and here are the terms it came back on: > until July 7 it's included in a plan and covers up to 50% of the weekly limit > after that only through credits, topped up in settings > output runs at 50 dollars per million tokens Anthropic says it's the same model, just with stronger protection against cybersecurity use. Because the filter is so strict, there will be false positives now and then, and a request will get bumped down to a weaker model Whether it's the same power or quietly trimmed will only show after a couple of weeks of real work

CLAUDE FABLE 5 IS BACK, BUT IS IT THE SAME POWER OR WAS IT QUIETLY TRIMMED Fable 5 is available again. Anthropic's most powerful model is back globally for every paid account When it first landed three weeks ago, the difference was obvious right away. It didn't just help, it carried the task to the finish: entire web projects, presentations, reports, analysis. People dropped their work on other models and simply waited for Fable And the wait happened because three days after launch the US hit the model with export controls. There was no clean way to cut off foreign nationals, so Anthropic shut access down for everyone Now the restrictions are lifted, and here are the terms it came back on: > until July 7 it's included in a plan and covers up to 50% of the weekly limit > after that only through credits, topped up in settings > output runs at 50 dollars per million tokens Anthropic says it's the same model, just with stronger protection against cybersecurity use. Because the filter is so strict, there will be false positives now and then, and a request will get bumped down to a weaker model Whether it's the same power or quietly trimmed will only show after a couple of weeks of real work

Mikadzyki🌙

20,003 görüntüleme • 24 gün önce

Openai giving $50,000 in FREE API credits and it's hidden in your account settings 😳 most people have no idea this exists what you get every single day: - 250K tokens/day for GPT-5.5 and GPT-5.2 (powerful models) - 2.5M tokens/day for GPT-5.1-Mini and GPT-5-Nano (lighter models) - up to 10M tokens/day if you're on tier 3-5 not a one time lump sum, it resets daily it's called the data sharing program and here's how it works: > go to > click data controls → sharing > opt in to both options > done, free daily tokens activate immediately important note: - your data gets used by openai for training and improvements - don't use it for client work or anything sensitive - need a positive account balance to activate perfect for: - learning and experimenting - side projects and personal builds - testing new models without paying you need a positive account balance to activate it but after that it's free every day save this and take free 50k credits before they close it

Openai giving $50,000 in FREE API credits and it's hidden in your account settings 😳 most people have no idea this exists what you get every single day: - 250K tokens/day for GPT-5.5 and GPT-5.2 (powerful models) - 2.5M tokens/day for GPT-5.1-Mini and GPT-5-Nano (lighter models) - up to 10M tokens/day if you're on tier 3-5 not a one time lump sum, it resets daily it's called the data sharing program and here's how it works: > go to > click data controls → sharing > opt in to both options > done, free daily tokens activate immediately important note: - your data gets used by openai for training and improvements - don't use it for client work or anything sensitive - need a positive account balance to activate perfect for: - learning and experimenting - side projects and personal builds - testing new models without paying you need a positive account balance to activate it but after that it's free every day save this and take free 50k credits before they close it

Isra

168,671 görüntüleme • 1 ay önce

$SITUATION EXPLAINED: Kimi K3 just beat Fable on a major coding benchmark, at a fraction of the price. • Kimi K3 beat Fable on Frontend Code Arena • The gap between Kimi and Fable is bigger than the gap between Fable and Sol • It also smashes Opus outright, while being priced the same as Sonnet, $3/$15 per million tokens • Sonnet 5 High currently sits in 10th place on this leaderboard at that same price point • The generational jump is dramatic: Kimi K2.6 ranked 18th on this benchmark, K3 jumped 17 spots to take the top spot • K3 ranked #1 in 6 of 7 tested domains: brand and marketing, reference-based design, data and analytics, consumer products, simulations, and content creation tools, it placed #2, only in gaming, behind Fable • Full model weights are set to release July 27th Theo Jaffee: "Imagine if Anthropic were a public company today, their stock would be down 20%, maybe more, enterprises are probably not gonna be spending $10 and $50 on Fable when they can instead be spending $3 and $15 on Kimi K3."$

SITUATION EXPLAINED: Kimi K3 just beat Fable on a major coding benchmark, at a fraction of the price. • Kimi K3 beat Fable on Frontend Code Arena • The gap between Kimi and Fable is bigger than the gap between Fable and Sol • It also smashes Opus outright, while being priced the same as Sonnet, $3/$15 per million tokens • Sonnet 5 High currently sits in 10th place on this leaderboard at that same price point • The generational jump is dramatic: Kimi K2.6 ranked 18th on this benchmark, K3 jumped 17 spots to take the top spot • K3 ranked #1 in 6 of 7 tested domains: brand and marketing, reference-based design, data and analytics, consumer products, simulations, and content creation tools, it placed #2, only in gaming, behind Fable • Full model weights are set to release July 27th Theo Jaffee: "Imagine if Anthropic were a public company today, their stock would be down 20%, maybe more, enterprises are probably not gonna be spending $10 and $50 on Fable when they can instead be spending $3 and $15 on Kimi K3."

MTS

132,110 görüntüleme • 9 gün önce

FREE DeepSeek V4 Pro and V4 Flash API. Runtime by Bad Theory Labs just dropped it. Same platform, new free model, same 2-minute setup. > Runtime already gave you free Claude Opus 4.8 and GPT 5.5 access. Now they added DeepSeek V4 Pro and V4 Flash to the free tier. Absolutely FREE, YES. Same exact flow as before: → Go to runtime(.)badtheorylabs(.)com → Sign up with Google → Fill in your details during onboarding → Free balance lands automatically(But you don't need it to use DeepSeek - it's completely free right now) → Grab your API key from the dashboard → Plug into OpenCode, OpenClaw, or Hermes - done DeepSeek V4 Pro is one of the strongest coding and reasoning models available right now. Free tier also includes btl-2 - auto-routes between GLM, OpenAI, Anthropic, and Gemma. 10 million tokens per month at zero cost. 344 models total. One OpenAI-compatible endpoint. No code rebuild, no card, no limits hunting. >> Just start using the API, and when choosing a provider, select DeepSeek I tested it myself - fully working. Bookmark this before the free tier fills up.

FREE DeepSeek V4 Pro and V4 Flash API. Runtime by Bad Theory Labs just dropped it. Same platform, new free model, same 2-minute setup. > Runtime already gave you free Claude Opus 4.8 and GPT 5.5 access. Now they added DeepSeek V4 Pro and V4 Flash to the free tier. Absolutely FREE, YES. Same exact flow as before: → Go to runtime(.)badtheorylabs(.)com → Sign up with Google → Fill in your details during onboarding → Free balance lands automatically(But you don't need it to use DeepSeek - it's completely free right now) → Grab your API key from the dashboard → Plug into OpenCode, OpenClaw, or Hermes - done DeepSeek V4 Pro is one of the strongest coding and reasoning models available right now. Free tier also includes btl-2 - auto-routes between GLM, OpenAI, Anthropic, and Gemma. 10 million tokens per month at zero cost. 344 models total. One OpenAI-compatible endpoint. No code rebuild, no card, no limits hunting. >> Just start using the API, and when choosing a provider, select DeepSeek I tested it myself - fully working. Bookmark this before the free tier fills up.

Atenov int.

26,920 görüntüleme • 1 ay önce

Nothing beats open-source! We now have a fully open-source coding agent that can compete with any proprietary solution out there: • 500+ available models • It doesn't train on your code • It doesn't charge a penny for tokens • It's open. You can change if you want. Kilo Code is the #1 app on OpenRouter right now, and the community is releasing new features on GitHub at rocket speed (about 20 releases in the last 30 days). I installed it in Visual Studio Code, but you can install it in pretty much any IDE. I need to spend more time with it, but here is a very interesting design choice: Most coding agents support two modes: an "agentic" mode for writing code and an "ask" mode for talking to the model without making any changes. Kilo Code supports 5 different modes: 1. Architect mode - Research, design, and planning 2. Debug mode - Problem solving and troubleshooting 3. Code mode - To write code. 4. Ask mode - To talk to the model. 5. Orchestrator mode - Combine every agent to solve problems. On paper, I really like this. I'll need more time to try out the specialized agents and see whether niching becomes an advantage. Here is the link to the website: Thanks to the Kilo for partnering with me on this post.

Nothing beats open-source! We now have a fully open-source coding agent that can compete with any proprietary solution out there: • 500+ available models • It doesn't train on your code • It doesn't charge a penny for tokens • It's open. You can change if you want. Kilo Code is the #1 app on OpenRouter right now, and the community is releasing new features on GitHub at rocket speed (about 20 releases in the last 30 days). I installed it in Visual Studio Code, but you can install it in pretty much any IDE. I need to spend more time with it, but here is a very interesting design choice: Most coding agents support two modes: an "agentic" mode for writing code and an "ask" mode for talking to the model without making any changes. Kilo Code supports 5 different modes: 1. Architect mode - Research, design, and planning 2. Debug mode - Problem solving and troubleshooting 3. Code mode - To write code. 4. Ask mode - To talk to the model. 5. Orchestrator mode - Combine every agent to solve problems. On paper, I really like this. I'll need more time to try out the specialized agents and see whether niching becomes an advantage. Here is the link to the website: Thanks to the Kilo for partnering with me on this post.

Santiago

73,062 görüntüleme • 8 ay önce

This is how you get 15x fable 5 usage. Fable -> Composer 2.5 reading Fable -> GPT 5.5 execution I built CNVS to make agent orchestration dead simple and insanely visual. You can watch fable 5 delegate work to cursor, codex, open code, all your agents. using your exsisting ai subs no api pricing. The canvas is fully voice controlled locally with nvidia parakeet for fast and free, or gpt realtime 2 for a fully conversational jarvis experience. The built in mcp and cli means agentic control is bidirectional they can prompt and spawn each other and read agent states. but there is more I built it from the ground up in swift for native performance on mac os. My old 16gb m1 mbp can easily spin up and control eight agents across multiple canvasses. The hermes integration + remote canvases allow you to run agents fully in the cloud on your VPS think google docs of vibe coding. You can literally turn off your mac and they keep working, open cnvs back up and pick up where you left off. I built a cross agent memory system based on 2026 research so all your agents feel like one brain. its SIMPLE and on demand. This eliminates context bloat, and the research supports a massive uptick in cross agent performance. There is soo much more. PS - I am a father building this project 100% solo in my basement on live stream everyday, my goal is to push vibe coding to the next level PPS - CNVS is a lifetime license becuase you DO NOT need another subscription in your life.

This is how you get 15x fable 5 usage. Fable -> Composer 2.5 reading Fable -> GPT 5.5 execution I built CNVS to make agent orchestration dead simple and insanely visual. You can watch fable 5 delegate work to cursor, codex, open code, all your agents. using your exsisting ai subs no api pricing. The canvas is fully voice controlled locally with nvidia parakeet for fast and free, or gpt realtime 2 for a fully conversational jarvis experience. The built in mcp and cli means agentic control is bidirectional they can prompt and spawn each other and read agent states. but there is more I built it from the ground up in swift for native performance on mac os. My old 16gb m1 mbp can easily spin up and control eight agents across multiple canvasses. The hermes integration + remote canvases allow you to run agents fully in the cloud on your VPS think google docs of vibe coding. You can literally turn off your mac and they keep working, open cnvs back up and pick up where you left off. I built a cross agent memory system based on 2026 research so all your agents feel like one brain. its SIMPLE and on demand. This eliminates context bloat, and the research supports a massive uptick in cross agent performance. There is soo much more. PS - I am a father building this project 100% solo in my basement on live stream everyday, my goal is to push vibe coding to the next level PPS - CNVS is a lifetime license becuase you DO NOT need another subscription in your life.

Max Blade

29,334 görüntüleme • 22 gün önce

FABLE 5 JUST REBUILT FORTNITE FROM 1 PROMPT IN 20 MINUTES. EPIC NEEDED HUNDREDS OF ENGINEERS AND 6 YEARS. The test was simple: Fable 5 vs GLM 5.2, one prompt each, a 100-player battle royale running in the browser with no engine and no team. GLM went first and checked all 8 milestones. The game loaded with a battle bus, a generated map, Tilted Towers, even health and shield bars ripped straight from 2018. Then it fell apart. 2 FPS on landing, S walking forward and W walking backward, a gun that fires upward and a camera that refuses to look up. First fight ended with the enemy standing above physically impossible to aim at. Then Fable 5 took the same prompt on max effort. Different game entirely. Real character models instead of beans, hit reactions lighting up on contact, a shadow tracking every player, movement that just works out of the box. One follow-up prompt “add more Fortnite elements” and it shipped gliders, chests, shield potions, medkits and a sniper without breaking a thing. Final circle at 3:28 AM. Storm closing, 0 bullets left, box to box with medkit spam and a last-second swap to the SMG. Victory Royale in a game an AI wrote from a single sentence. GLM checked more boxes. Fable built something you could actually play and no benchmark on earth measures that gap. Epic needed 6 years. Fable 5 needed 1 prompt.

FABLE 5 JUST REBUILT FORTNITE FROM 1 PROMPT IN 20 MINUTES. EPIC NEEDED HUNDREDS OF ENGINEERS AND 6 YEARS. The test was simple: Fable 5 vs GLM 5.2, one prompt each, a 100-player battle royale running in the browser with no engine and no team. GLM went first and checked all 8 milestones. The game loaded with a battle bus, a generated map, Tilted Towers, even health and shield bars ripped straight from 2018. Then it fell apart. 2 FPS on landing, S walking forward and W walking backward, a gun that fires upward and a camera that refuses to look up. First fight ended with the enemy standing above physically impossible to aim at. Then Fable 5 took the same prompt on max effort. Different game entirely. Real character models instead of beans, hit reactions lighting up on contact, a shadow tracking every player, movement that just works out of the box. One follow-up prompt “add more Fortnite elements” and it shipped gliders, chests, shield potions, medkits and a sniper without breaking a thing. Final circle at 3:28 AM. Storm closing, 0 bullets left, box to box with medkit spam and a last-second swap to the SMG. Victory Royale in a game an AI wrote from a single sentence. GLM checked more boxes. Fable built something you could actually play and no benchmark on earth measures that gap. Epic needed 6 years. Fable 5 needed 1 prompt.

West Lord

80,912 görüntüleme • 23 gün önce

GPT-Realtime 2 is the future of the operating system. I've been experimenting with it for a couple weeks now, and I gotta say, it's pretty gosh darn incredible. Opening apps, searching the web, even editing in Premiere. All with just my voice. And it only takes a few prompts to set up. In this video I'll show you exactly how. 0:00 Intro 1:46 What is GPT-Realtime 2? 4:46 Setting it up (no coding) 7:53 Fixing the always-on mic (push-to-talk) 9:41 Demo: searching the web 11:38 Demo: connecting apps via MCP (Obsidian) 14:13 Demo: controlling Premiere Pro (accessibility tree) 18:00 Honest caveats 19:00 Outro

GPT-Realtime 2 is the future of the operating system. I've been experimenting with it for a couple weeks now, and I gotta say, it's pretty gosh darn incredible. Opening apps, searching the web, even editing in Premiere. All with just my voice. And it only takes a few prompts to set up. In this video I'll show you exactly how. 0:00 Intro 1:46 What is GPT-Realtime 2? 4:46 Setting it up (no coding) 7:53 Fixing the always-on mic (push-to-talk) 9:41 Demo: searching the web 11:38 Demo: connecting apps via MCP (Obsidian) 14:13 Demo: controlling Premiere Pro (accessibility tree) 18:00 Honest caveats 19:00 Outro

Pat Simmons

605,341 görüntüleme • 1 ay önce

NVIDIA QUIETLY DROPPED A $249 BOX THAT REPLACES YOUR $200/MONTH OPENAI SUBSCRIPTION WITH $2 IN ELECTRICITY it's called the jetson orin nano super. smaller than a wallet, runs at 25 watts, does 70 trillion ai operations per second. runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even in 10 weeks install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically 7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. total monthly cost drops from $200 to $22 cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027 bookmark this and read the article below

NVIDIA QUIETLY DROPPED A $249 BOX THAT REPLACES YOUR $200/MONTH OPENAI SUBSCRIPTION WITH $2 IN ELECTRICITY it's called the jetson orin nano super. smaller than a wallet, runs at 25 watts, does 70 trillion ai operations per second. runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even in 10 weeks install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically 7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. total monthly cost drops from $200 to $22 cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027 bookmark this and read the article below

starmex

2,353,719 görüntüleme • 2 ay önce

Alibaba just dropped Qwen3.5-397B-A17B and there's a lot to unpack. 397B params, 17B active per forward pass. Sparse MoE done right. But the real story isn't the size—it's the architecture choices. The MoE Design Most MoE models feel like bolt-ons. Qwen 3.5's sparse activation is native—only 4.3% of parameters fire per token. That's how you get trillion-parameter-class performance without trillion-parameter inference costs. The 0.8 RMB/million tokens pricing isn't subsidized; it's structurally earned. Native Multimodal, Not Glued-On This is a vision-language model from the ground up. Heterogeneous architecture—separate processing pipelines for text, image, video that fuse early. Not a vision encoder slapped onto an LLM. The result: 90.8 on OmniDocBench, 79.0 on MMMU-Pro. Document understanding and visual reasoning without the usual brittleness. The Context Window Reality Qwen3.5-Plus (the hosted version) ships with 1M tokens by default. That's not a marketing number—they're actually positioning it for long-document workflows. With built-in adaptive tool use, it's clearly aimed at agentic automation, not just chat. What Actually Impressed Me • FP8 native pipeline: ~50% activation memory reduction • Async RL framework for continuous refinement—training and inference workloads separated • 201 languages (up from 119), 250k vocab for better low-resource encoding • Apache 2.0 license. Full weights on HuggingFace and ModelScope. The Benchmark Context 76.4 on SWE-bench Verified puts it in the range where it can handle real debugging workflows. 72.9 on BFCL v4 for agentic tool use. 88.4 on GPQA Diamond. These aren't SOTA in isolation, but the breadth is unusual—strong across reasoning, coding, multimodal, and agentic tasks. The Honest Caveat I haven't stress-tested the 1M context for needle-in-haystack retrieval yet. And "native multimodal" claims need real-world torture testing—PDFs with tables, charts, mixed layouts. Benchmarks are benchmarks. Bottom Line This isn't just another model release. It's a bet on efficient scale: big model capabilities, small active compute, open weights. At 1/18th the cost of Gemini 3 Pro, it's going to force pricing conversations across the board.

Alibaba just dropped Qwen3.5-397B-A17B and there's a lot to unpack. 397B params, 17B active per forward pass. Sparse MoE done right. But the real story isn't the size—it's the architecture choices. The MoE Design Most MoE models feel like bolt-ons. Qwen 3.5's sparse activation is native—only 4.3% of parameters fire per token. That's how you get trillion-parameter-class performance without trillion-parameter inference costs. The 0.8 RMB/million tokens pricing isn't subsidized; it's structurally earned. Native Multimodal, Not Glued-On This is a vision-language model from the ground up. Heterogeneous architecture—separate processing pipelines for text, image, video that fuse early. Not a vision encoder slapped onto an LLM. The result: 90.8 on OmniDocBench, 79.0 on MMMU-Pro. Document understanding and visual reasoning without the usual brittleness. The Context Window Reality Qwen3.5-Plus (the hosted version) ships with 1M tokens by default. That's not a marketing number—they're actually positioning it for long-document workflows. With built-in adaptive tool use, it's clearly aimed at agentic automation, not just chat. What Actually Impressed Me • FP8 native pipeline: ~50% activation memory reduction • Async RL framework for continuous refinement—training and inference workloads separated • 201 languages (up from 119), 250k vocab for better low-resource encoding • Apache 2.0 license. Full weights on HuggingFace and ModelScope. The Benchmark Context 76.4 on SWE-bench Verified puts it in the range where it can handle real debugging workflows. 72.9 on BFCL v4 for agentic tool use. 88.4 on GPQA Diamond. These aren't SOTA in isolation, but the breadth is unusual—strong across reasoning, coding, multimodal, and agentic tasks. The Honest Caveat I haven't stress-tested the 1M context for needle-in-haystack retrieval yet. And "native multimodal" claims need real-world torture testing—PDFs with tables, charts, mixed layouts. Benchmarks are benchmarks. Bottom Line This isn't just another model release. It's a bet on efficient scale: big model capabilities, small active compute, open weights. At 1/18th the cost of Gemini 3 Pro, it's going to force pricing conversations across the board.

Bo Wang

13,221 görüntüleme • 5 ay önce