Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

🌘 Meet Kimi K2.7 Code HighSpeed! A high-speed mode of our latest open-source multimodal coding model, Kimi K2.7 Code. ⚡️ Up to 6× faster: Around 180 tok/s on coding tasks with median-length inputs, and up to 260 tok/s on shorter-context tasks. 🔷 Rolling out to Kimi Code Beta Program...

Kimi_Moonshot's profile picture

Kimi.ai

182,914 subscribers

526,090 Aufrufe • vor 1 Monat •via X (Twitter)

BildungNachrichten & PolitikWissenschaft & Technologie
LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

🆕 Kimi.ai's Kimi K2.7 Code is now generally available in GitHub Copilot. This is the first open-weight model offered as a selectable option in the Copilot model picker. 🎉 Early testing shows Kimi K2.7 is a lower-cost option with strong performance comparable to highly popular frontier models. Try it out now in Visual Studio Code and look out for it in more GitHub Copilot surfaces. 👇
0:55

🆕 Kimi.ai's Kimi K2.7 Code is now generally available in GitHub Copilot. This is the first open-weight model offered as a selectable option in the Copilot model picker. 🎉 Early testing shows Kimi K2.7 is a lower-cost option with strong performance comparable to highly popular frontier models. Try it out now in Visual Studio Code and look out for it in more GitHub Copilot surfaces. 👇

GitHub

194,652 Aufrufe • vor 14 Tagen

Cline has launched ClinePass, a flat monthly subscription that opens access to a curated set of open-weight coding models across its IDE extensions, CLI, and SDK. The current lineup includes GLM 5.2, Kimi K2.7 Code, DeepSeek V4 Pro, MiniMax-M3, and Qwen3.7, with a subscription replacing separate API keys across providers.
0:38

Cline has launched ClinePass, a flat monthly subscription that opens access to a curated set of open-weight coding models across its IDE extensions, CLI, and SDK. The current lineup includes GLM 5.2, Kimi K2.7 Code, DeepSeek V4 Pro, MiniMax-M3, and Qwen3.7, with a subscription replacing separate API keys across providers.

🚨 AI News | TestingCatalog

54,728 Aufrufe • vor 17 Tagen

Anthropic's in trouble, again. The entire Claude experience is now available at 1/6th the price. Kimi now does everything Claude does, powered by K2.6, a 1-trillion-parameter MoE model that activates only 32B parameters per token. It covers all three features Claude has (Chat, Code, and Cowork): 1) Kimi Chat runs in four modes - Instant for fast responses - Thinking for deep reasoning - Agent for multi-step execution - and Agent Swarm for parallel workloads. There's a 262K context window across all of them. 2) Kimi Code is the open-source CLI coding agent with K2.6 as the default backend. K2.6 ranked #1 on OpenRouter's programming leaderboard by weekly usage. 3) Kimi Agent is the Cowork equivalent. It generates: - full websites with database and auth - presentation decks (editable PPTX output) - spreadsheets with formulas and charts - word docs and structured research reports. On top of this, Kimi K2.6 is also trained to decompose tasks into up to 300 parallel sub-agents. This helps it retain coherence even across 4,000+ tool calls in a single run, with sessions sustaining up to 13 hours. On SWE-Bench Pro: - Kimi K2.6 → 58.6 - GPT-5.4 xhigh → 57.7 - Gemini 3.1 Pro → 54.2 - Claude Opus 4.6 → 53.4 Kimi K2.6 model is open weights and self-hostable on 4x H100s in INT4. Find the link to the HuggingFace model page in the replies!
0:41

Anthropic's in trouble, again. The entire Claude experience is now available at 1/6th the price. Kimi now does everything Claude does, powered by K2.6, a 1-trillion-parameter MoE model that activates only 32B parameters per token. It covers all three features Claude has (Chat, Code, and Cowork): 1) Kimi Chat runs in four modes - Instant for fast responses - Thinking for deep reasoning - Agent for multi-step execution - and Agent Swarm for parallel workloads. There's a 262K context window across all of them. 2) Kimi Code is the open-source CLI coding agent with K2.6 as the default backend. K2.6 ranked #1 on OpenRouter's programming leaderboard by weekly usage. 3) Kimi Agent is the Cowork equivalent. It generates: - full websites with database and auth - presentation decks (editable PPTX output) - spreadsheets with formulas and charts - word docs and structured research reports. On top of this, Kimi K2.6 is also trained to decompose tasks into up to 300 parallel sub-agents. This helps it retain coherence even across 4,000+ tool calls in a single run, with sessions sustaining up to 13 hours. On SWE-Bench Pro: - Kimi K2.6 → 58.6 - GPT-5.4 xhigh → 57.7 - Gemini 3.1 Pro → 54.2 - Claude Opus 4.6 → 53.4 Kimi K2.6 model is open weights and self-hostable on 4x H100s in INT4. Find the link to the HuggingFace model page in the replies!

Avi Chawla

109,238 Aufrufe • vor 2 Monaten

So Alibaba has just released a coding plan with all the best open source models You’ve access to Qwen 3.5-Plus, Kimi K2.5, MiniMax M2.5, GLM-5, etc. And you can plug it to: - Claude Code (as I did) - OpenClaw - Codex - Cline… While being waaay cheaper than the paid plan of Codex, Claude & Cie. More below
0:36

So Alibaba has just released a coding plan with all the best open source models You’ve access to Qwen 3.5-Plus, Kimi K2.5, MiniMax M2.5, GLM-5, etc. And you can plug it to: - Claude Code (as I did) - OpenClaw - Codex - Cline… While being waaay cheaper than the paid plan of Codex, Claude & Cie. More below

Paul Couvert

88,326 Aufrufe • vor 4 Monaten

NVIDIA is giving away free access to 140+ AI models for a full year > most people building AI agents are paying $50-200/month for API access NVIDIA just made that argument irrelevant models you get: GLM 5.2, MiniMax M3, Nemotron-3-Ultra-550B-A55B, Kimi K2.7, and 130+ more setup: > step 1 - get your free key > go to > register -> bind phone -> copy API key > step 2 - add to Hermes agent > open Settings -> Model Provider -> Custom base_url = " api_key = "nvapi-xxxxxxxxxxxxxxxxxxxx" > step 3 - pick a model model = "z-ai/glm-5.2" model = "minimaxai/minimax-m3" model = "nvidia/nemotron-3-ultra-550b-a55b" model = "moonshot-ai/kimi-k2.7" > Hermes already has NVIDIA set as default base_url > paste the key and you're running instantly > works the same in Cursor and OpenCode > cost: $0 > limit: 40 req/min > expires: 1 year while everyone is paying for API access, this is sitting there for free with this many models in one place, it is also the easiest way to test which one actually fits your agent before you commit to a paid provider
0:29

NVIDIA is giving away free access to 140+ AI models for a full year > most people building AI agents are paying $50-200/month for API access NVIDIA just made that argument irrelevant models you get: GLM 5.2, MiniMax M3, Nemotron-3-Ultra-550B-A55B, Kimi K2.7, and 130+ more setup: > step 1 - get your free key > go to > register -> bind phone -> copy API key > step 2 - add to Hermes agent > open Settings -> Model Provider -> Custom base_url = " api_key = "nvapi-xxxxxxxxxxxxxxxxxxxx" > step 3 - pick a model model = "z-ai/glm-5.2" model = "minimaxai/minimax-m3" model = "nvidia/nemotron-3-ultra-550b-a55b" model = "moonshot-ai/kimi-k2.7" > Hermes already has NVIDIA set as default base_url > paste the key and you're running instantly > works the same in Cursor and OpenCode > cost: $0 > limit: 40 req/min > expires: 1 year while everyone is paying for API access, this is sitting there for free with this many models in one place, it is also the easiest way to test which one actually fits your agent before you commit to a paid provider

Mr. Buzzoni

77,395 Aufrufe • vor 2 Tagen

THIS GUY USED OPUS 4.8 + KIMI K2.6 TO CUT HIS CODING BILL FROM $4,000 TO $700/MO. WITH KIMI RUNNING A 300-AGENT CODING FLOOR, HE STOPPED PAYING CLAUDE TO DO EVERYTHING kimi does the cheap heavy lifting. it can spin up hundreds of agents, push through thousands of steps, write the rough code, expand files, draft tests and handle the repetitive work that burns the most tokens opus 4.8 only comes in where the money is worth spending. first to plan the spec and define the rules, then again to tear apart the output, catch weak logic and flag the bugs that a fast swarm can miss that is what changed the economics. kimi handled the bulk of the volume for a fraction of the price, while opus stayed in the loop as the architect and the reviewer instead of the full-time builder most people still use one model for every step and wonder why their costs explode. this guy split the jobs properly. kimi runs wide and cheap. opus goes deep and skeptical. one builds fast, the other makes sure it should ship the real edge is not finding one perfect model. it is knowing where expensive intelligence actually matters and where cheap parallel output is already enough. that is how a $4,000 workflow turns into a $700 system
1:28

THIS GUY USED OPUS 4.8 + KIMI K2.6 TO CUT HIS CODING BILL FROM $4,000 TO $700/MO. WITH KIMI RUNNING A 300-AGENT CODING FLOOR, HE STOPPED PAYING CLAUDE TO DO EVERYTHING kimi does the cheap heavy lifting. it can spin up hundreds of agents, push through thousands of steps, write the rough code, expand files, draft tests and handle the repetitive work that burns the most tokens opus 4.8 only comes in where the money is worth spending. first to plan the spec and define the rules, then again to tear apart the output, catch weak logic and flag the bugs that a fast swarm can miss that is what changed the economics. kimi handled the bulk of the volume for a fraction of the price, while opus stayed in the loop as the architect and the reviewer instead of the full-time builder most people still use one model for every step and wonder why their costs explode. this guy split the jobs properly. kimi runs wide and cheap. opus goes deep and skeptical. one builds fast, the other makes sure it should ship the real edge is not finding one perfect model. it is knowing where expensive intelligence actually matters and where cheap parallel output is already enough. that is how a $4,000 workflow turns into a $700 system

Gipp 🦅

16,989 Aufrufe • vor 1 Monat

✨ Expansion Phase: Get your Access Code to the Closed Beta We’ve successfully completed the first phase of testing, and now it’s time for new players to enter the Pixelverse. Access Codes are being released—are you ready to claim yours? 🔓 How to get access? - Be Engaged! We’re rewarding our most active community members across Discord, Twitter, and PixelTap starting right now! - Stay Alert! Keep an eye on official announcements, the fastest and most engaged users will be rewarded with codes. - Redeem & Enter: Activate your Access Code in the Dashboard and jump into the Pixelverse! 🖼 NFT Holders Get Priority: Holding a Pixelverse NFT gives you a higher chance of securing an Access Code. ⏳ Act Fast and claim your place in Pixelverse! Only a limited number of Access Codes are being distributed. 🧠 And don’t forget—the Quest-Based Airdrop is coming soon! Secure your access now and get ready to unlock $PIXFI through in-game quests! ➡ Join Discord: DISCORD
0:59

✨ Expansion Phase: Get your Access Code to the Closed Beta We’ve successfully completed the first phase of testing, and now it’s time for new players to enter the Pixelverse. Access Codes are being released—are you ready to claim yours? 🔓 How to get access? - Be Engaged! We’re rewarding our most active community members across Discord, Twitter, and PixelTap starting right now! - Stay Alert! Keep an eye on official announcements, the fastest and most engaged users will be rewarded with codes. - Redeem & Enter: Activate your Access Code in the Dashboard and jump into the Pixelverse! 🖼 NFT Holders Get Priority: Holding a Pixelverse NFT gives you a higher chance of securing an Access Code. ⏳ Act Fast and claim your place in Pixelverse! Only a limited number of Access Codes are being distributed. 🧠 And don’t forget—the Quest-Based Airdrop is coming soon! Secure your access now and get ready to unlock $PIXFI through in-game quests! ➡ Join Discord: DISCORD

Pixelverse

294,071 Aufrufe • vor 1 Jahr

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.
6:17

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 Aufrufe • vor 8 Monaten

Cerebras inference is very fast. So fast that it changes how we think about configuring our LLMs for voice agent use cases. Kimi K2.6 is a 1T parameter reasoning model that Cerebras serves at 650 - 1,000 tokens per second (end-to-end throughput), with time to first token metrics as low as 150ms (latency). These numbers are two to three times faster than other similarly capable models. The biggest lever we get from this kind of speed is that we can use the model in reasoning mode, and still have excellent "time to first non-thinking token." This solves a big pain point we have in 2026 for voice agent use cases. Almost all recent innovation in post-training has focused on making models good at reasoning ("test time compute"). This is great, but it makes the user-facing model latency much, much slower. Which is a problem for conversational voice agents. We can run Kimi K2.6 with reasoning turned on, and get responses faster than other models produce with reasoning disabled. On my 30-turn voice agent benchmark, Kimi K2.6 with reasoning enabled ties GPT 5.1 and Haiku 4.5 with reasoning disabled, and is still about 200ms seconds faster! On my primary task agent benchmark, Kimi K2.6 is now the #2 model. It ranks just behind Gemini 3.5 Flash in "high" reasoning mode, and tied with GLM 5, Sonnet 4.6, and GPT 5.4 with reasoning set to "low." But Kimi K2.6 completes each turn in the agent loop in under 500ms. The other four models are all at least 3x slower. (Models only qualify for this benchmark if they can complete task turns at a P50 <4s.) A couple of other things that this speed buys us, for production voice agents: - Tool calls happen fast enough that we don't have to work around tool call latency in our pipeline design. - We can prompt the model to output structured data at the beginning of a response, followed by plain text for voice generation. This opens up possibilities like asking the model to do complex classification/generation tasks that influence the rest of the pipeline. For example, the model could create a detailed style prompt for a steerable TTS model, for each individual conversation turn. And, of course, you can use Kimi K2.6 with reasoning turned off. Cerebras calls this "instant" mode. Here's a video of a Cerebras Kimi K2.6 voice agent with voice-to-voice response time, measured at the client, under 500ms. This is the true response latency as perceived by the user, including all network and audio codec overhead, transcription and turn detection, Kimi K2.6 token generation, and voice generation. 500ms is, effectively, instant. So the Cerebras naming for this mode is a propos. :-)
0:40

Cerebras inference is very fast. So fast that it changes how we think about configuring our LLMs for voice agent use cases. Kimi K2.6 is a 1T parameter reasoning model that Cerebras serves at 650 - 1,000 tokens per second (end-to-end throughput), with time to first token metrics as low as 150ms (latency). These numbers are two to three times faster than other similarly capable models. The biggest lever we get from this kind of speed is that we can use the model in reasoning mode, and still have excellent "time to first non-thinking token." This solves a big pain point we have in 2026 for voice agent use cases. Almost all recent innovation in post-training has focused on making models good at reasoning ("test time compute"). This is great, but it makes the user-facing model latency much, much slower. Which is a problem for conversational voice agents. We can run Kimi K2.6 with reasoning turned on, and get responses faster than other models produce with reasoning disabled. On my 30-turn voice agent benchmark, Kimi K2.6 with reasoning enabled ties GPT 5.1 and Haiku 4.5 with reasoning disabled, and is still about 200ms seconds faster! On my primary task agent benchmark, Kimi K2.6 is now the #2 model. It ranks just behind Gemini 3.5 Flash in "high" reasoning mode, and tied with GLM 5, Sonnet 4.6, and GPT 5.4 with reasoning set to "low." But Kimi K2.6 completes each turn in the agent loop in under 500ms. The other four models are all at least 3x slower. (Models only qualify for this benchmark if they can complete task turns at a P50 <4s.) A couple of other things that this speed buys us, for production voice agents: - Tool calls happen fast enough that we don't have to work around tool call latency in our pipeline design. - We can prompt the model to output structured data at the beginning of a response, followed by plain text for voice generation. This opens up possibilities like asking the model to do complex classification/generation tasks that influence the rest of the pipeline. For example, the model could create a detailed style prompt for a steerable TTS model, for each individual conversation turn. And, of course, you can use Kimi K2.6 with reasoning turned off. Cerebras calls this "instant" mode. Here's a video of a Cerebras Kimi K2.6 voice agent with voice-to-voice response time, measured at the client, under 500ms. This is the true response latency as perceived by the user, including all network and audio codec overhead, transcription and turn detection, Kimi K2.6 token generation, and voice generation. 500ms is, effectively, instant. So the Cerebras naming for this mode is a propos. :-)

kwindla

40,319 Aufrufe • vor 1 Monat

Announcing Opcode Everyone's favorite Claude Code GUI Claudia is now Opcode... with a complete revamp. And we just hit 15K+ stars on GitHub! The support from the community has been immense! ❤️ What's new: - Feature parity with all new Claude Code features in the CLI. - A complete UI revamp, faster and cleaner. What's coming: - Opcode's own coding agent that exclusively uses open models while achieving SOTA performance on coding benchmarks. We're currently piloting this at companies requiring fully local on-prem coding agents. If you're one of them, reach out to us and we'll set this up for you! Try Opcode at opcode [dot] sh Like/retweet and reply to this tweet with "join" to get an invite to the Discord server and beta test our coding agent for free.
2:58

Announcing Opcode Everyone's favorite Claude Code GUI Claudia is now Opcode... with a complete revamp. And we just hit 15K+ stars on GitHub! The support from the community has been immense! ❤️ What's new: - Feature parity with all new Claude Code features in the CLI. - A complete UI revamp, faster and cleaner. What's coming: - Opcode's own coding agent that exclusively uses open models while achieving SOTA performance on coding benchmarks. We're currently piloting this at companies requiring fully local on-prem coding agents. If you're one of them, reach out to us and we'll set this up for you! Try Opcode at opcode [dot] sh Like/retweet and reply to this tweet with "join" to get an invite to the Discord server and beta test our coding agent for free.

winfunc

38,639 Aufrufe • vor 10 Monaten

Kimi K2.7-Code is now available on AI/ML API! Moonshot's latest is built for long-horizon agentic coding that self-corrects instead of one-shotting. So we gave it a hard one. SpaceX is going public, a company built on one habit: fly, fail, fix, fly again. That loop carried Falcon to the droneship and Starship toward orbit. We wanted to see if a model could run that same loop on its own. We gave four Kimi agents a 2D flight-physics sim they can't modify and one goal: reach orbit and land the booster on a droneship. Flight 1 broke up at max-Q. Flight 2 cleared max-Q but staged too early and fell back short of orbit. Flight 3 made orbit, then missed the droneship and hit the water. Flight 4 fixed the landing math and put the booster on the ship. Four flights, each failure feeding the next fix. The interesting result isn't the rocket, it's the closed-loop debugging. Architecture in the comments. Got any ideas for droneship name?
0:50

Kimi K2.7-Code is now available on AI/ML API! Moonshot's latest is built for long-horizon agentic coding that self-corrects instead of one-shotting. So we gave it a hard one. SpaceX is going public, a company built on one habit: fly, fail, fix, fly again. That loop carried Falcon to the droneship and Starship toward orbit. We wanted to see if a model could run that same loop on its own. We gave four Kimi agents a 2D flight-physics sim they can't modify and one goal: reach orbit and land the booster on a droneship. Flight 1 broke up at max-Q. Flight 2 cleared max-Q but staged too early and fell back short of orbit. Flight 3 made orbit, then missed the droneship and hit the water. Flight 4 fixed the landing math and put the booster on the ship. Four flights, each failure feeding the next fix. The interesting result isn't the rocket, it's the closed-loop debugging. Architecture in the comments. Got any ideas for droneship name?

AI/ML API

22,015 Aufrufe • vor 1 Monat

I'm giving away Claude Code for FREE. Yes, you read that right -- the world's best AI, now completely FREE. My mission is to get the next billion people to write great software. I believe EVERYONE should have access to the best AI, but so many are constrained by costs. I'm solving this by: disrupting the world's fastest growing industry = AI + with the most proven business model = Ads You can actually try it out now -- just one line of code, and you unlock all the powers of Claude Code, for free. how it works: 1. sign up on Giga AI Free 2. change Claude Code env variables to use our inference endpoint 2. to support the free usage, we'll add ads inside the AI responses (only contextual and relevant ads, no spam) Since we get too many signups, there's a waitlist, but we'll be rolling it out to the maximum people as we can. Watch the video to get started & comment and retweet to get access first.
0:51

I'm giving away Claude Code for FREE. Yes, you read that right -- the world's best AI, now completely FREE. My mission is to get the next billion people to write great software. I believe EVERYONE should have access to the best AI, but so many are constrained by costs. I'm solving this by: disrupting the world's fastest growing industry = AI + with the most proven business model = Ads You can actually try it out now -- just one line of code, and you unlock all the powers of Claude Code, for free. how it works: 1. sign up on Giga AI Free 2. change Claude Code env variables to use our inference endpoint 2. to support the free usage, we'll add ads inside the AI responses (only contextual and relevant ads, no spam) Since we get too many signups, there's a waitlist, but we'll be rolling it out to the maximum people as we can. Watch the video to get started & comment and retweet to get access first.

Namanyay

486,936 Aufrufe • vor 8 Monaten

Inviting early beta testers for our upcoming SWE agent, Asteria. We're solving AI code comprehension, where the context window and the size of your codebase are no longer limitations, and reinventing the UX of how coding agents are currently implemented. We initially built this to address false positives and enhance accuracy for our SAST agent, which autonomously identifies security vulnerabilities, traces how a payload would flow through code, and ultimately demonstrates an actual exploit. The performance improved so significantly that we decided to test it on realistic engineering tasks on large codebases and witnessed SOTA results. Reply "access" if you'd like to be an early beta tester, a lot of quirks to fix.
0:45

Inviting early beta testers for our upcoming SWE agent, Asteria. We're solving AI code comprehension, where the context window and the size of your codebase are no longer limitations, and reinventing the UX of how coding agents are currently implemented. We initially built this to address false positives and enhance accuracy for our SAST agent, which autonomously identifies security vulnerabilities, traces how a payload would flow through code, and ultimately demonstrates an actual exploit. The performance improved so significantly that we decided to test it on realistic engineering tasks on large codebases and witnessed SOTA results. Reply "access" if you'd like to be an early beta tester, a lot of quirks to fix.

mufeed vh

12,408 Aufrufe • vor 1 Jahr

🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.
0:48

🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.

AI Frontliner

60,126 Aufrufe • vor 5 Monaten

We’re releasing our Code Migration benchmark — and we managed to get Fable tested in time Code migration carries real economic weight. COBOL powers banks, payrolls, government services, and underpins nearly 95% of US ATM transactions. The danger with any migration is that a model ships code that looks right but quietly drops essential behaviors We evaluated models in three ways: modern to modern migrations, legacy to modern migrations and on their overall code quality. Each model rebuilds the program in an offline sandbox, then is scored on a hidden behavior test with anti-cheat checks that catch anything wrapping the original, copying reference files, or staying in the source language Fable 5 leads overall at 55%, but costs $115.43 per test, while Opus 4.8 (47%), and GPT 5.5 (45%) cost $30.51 and $6.44, respectively, making GPT 5.5 the most cost efficient model. Kimi K2.6 is the #1 open-weight model (28%) priced at $5.12, ranking above some frontier models
1:57

We’re releasing our Code Migration benchmark — and we managed to get Fable tested in time Code migration carries real economic weight. COBOL powers banks, payrolls, government services, and underpins nearly 95% of US ATM transactions. The danger with any migration is that a model ships code that looks right but quietly drops essential behaviors We evaluated models in three ways: modern to modern migrations, legacy to modern migrations and on their overall code quality. Each model rebuilds the program in an offline sandbox, then is scored on a hidden behavior test with anti-cheat checks that catch anything wrapping the original, copying reference files, or staying in the source language Fable 5 leads overall at 55%, but costs $115.43 per test, while Opus 4.8 (47%), and GPT 5.5 (45%) cost $30.51 and $6.44, respectively, making GPT 5.5 the most cost efficient model. Kimi K2.6 is the #1 open-weight model (28%) priced at $5.12, ranking above some frontier models

Vals AI

16,686 Aufrufe • vor 29 Tagen

MiniMax M2.1 is really good for writing code. It's open source, and you can connect Visual Studio Code to it and start coding right away. The model is especially good for those who don't use Python as a primary language. It's currently the best multilingual model out there. The model hits 72.5% on SWE-Multilingual and 88.6% on VIBE-Bench (best!) This means the model is also really good at performing real engineering work and does very well at agentic tasks: • Long tool chains • Structured agent scaffolding • Following repo-level rules and slash commands • Working inside existing agent frameworks without falling apart And obviously, it's faster, cheaper, and more concise than M2, which was already really good. I recorded a video to show you how to run MiniMax (official)'s 2.1 using Visual Studio Code.
5:45

MiniMax M2.1 is really good for writing code. It's open source, and you can connect Visual Studio Code to it and start coding right away. The model is especially good for those who don't use Python as a primary language. It's currently the best multilingual model out there. The model hits 72.5% on SWE-Multilingual and 88.6% on VIBE-Bench (best!) This means the model is also really good at performing real engineering work and does very well at agentic tasks: • Long tool chains • Structured agent scaffolding • Following repo-level rules and slash commands • Working inside existing agent frameworks without falling apart And obviously, it's faster, cheaper, and more concise than M2, which was already really good. I recorded a video to show you how to run MiniMax (official)'s 2.1 using Visual Studio Code.

Santiago

47,879 Aufrufe • vor 5 Monaten

The MiniMax M2 model is mind-blowing! It's open-source. It outperforms Gemini 2.5, Claude 4.1, and Qwen3 across coding and tool-use benchmarks. Right now, it's one of the world's top 5 models in intelligence! And here is the best part: Claude is one of the best models you can use today, and MiniMax M2 costs only 8% of that! It's smaller, faster, and cheaper. Extremely efficient at using tokens. Minimax M2's biggest strength: High agentic capabilities. The model can plan and execute complex multi-tool workflows. It's reliable and very robust at executing long-horizon tool chains. In summary: • Low latency • Very cheap • Excels at agentic tasks • Open-source The model currently powers the MiniMax Agent and is available for a free global trial. You can access MiniMax M2's API here: To access the agent: And here is the MiniMax website: Thanks to the MiniMax team for showing me the ropes and partnering with me on this post.
6:01

The MiniMax M2 model is mind-blowing! It's open-source. It outperforms Gemini 2.5, Claude 4.1, and Qwen3 across coding and tool-use benchmarks. Right now, it's one of the world's top 5 models in intelligence! And here is the best part: Claude is one of the best models you can use today, and MiniMax M2 costs only 8% of that! It's smaller, faster, and cheaper. Extremely efficient at using tokens. Minimax M2's biggest strength: High agentic capabilities. The model can plan and execute complex multi-tool workflows. It's reliable and very robust at executing long-horizon tool chains. In summary: • Low latency • Very cheap • Excels at agentic tasks • Open-source The model currently powers the MiniMax Agent and is available for a free global trial. You can access MiniMax M2's API here: To access the agent: And here is the MiniMax website: Thanks to the MiniMax team for showing me the ropes and partnering with me on this post.

Santiago

91,142 Aufrufe • vor 8 Monaten

Using Claude Pro credits no longer works on OpenClaw! Many heavy OpenClaw users were signing up for Claude Code subscriptions and then using their OAuth tokens to power the virtual assistant. But what was once a gray area is now an explicit violation of Anthropic policy. Users can no longer use their tokens in a third party tool as a work-around for not having to pay per use! What happens now? Will everyone start shifting to the cheaper Chinese models like Kimi?
3:21

Using Claude Pro credits no longer works on OpenClaw! Many heavy OpenClaw users were signing up for Claude Code subscriptions and then using their OAuth tokens to power the virtual assistant. But what was once a gray area is now an explicit violation of Anthropic policy. Users can no longer use their tokens in a third party tool as a work-around for not having to pay per use! What happens now? Will everyone start shifting to the cheaper Chinese models like Kimi?

This Week in Startups

13,103 Aufrufe • vor 4 Monaten

GLM 4.7 is one of the strongest open-source coding models available—but most developers aren't prompting it correctly. We put together 10 rules to help you get the most out of it: - Front-load instructions (it has a strong recency bias) - Use firm language: "must" and "strictly" > soft suggestions - Break complex tasks into smaller steps - Disable reasoning for simple tasks, enable it for hard ones - Use critic agents for code review, QA, and validation - Pair it with a frontier model for the hardest 10% of workloads - and more… GLM 4.7 hits 96% on Tau² Bench and 86% on GPQA Diamond. At 1,500 tokens/sec on Cerebras, it's 20x faster than closed-source alternatives on GPUs.
5:30

GLM 4.7 is one of the strongest open-source coding models available—but most developers aren't prompting it correctly. We put together 10 rules to help you get the most out of it: - Front-load instructions (it has a strong recency bias) - Use firm language: "must" and "strictly" > soft suggestions - Break complex tasks into smaller steps - Disable reasoning for simple tasks, enable it for hard ones - Use critic agents for code review, QA, and validation - Pair it with a frontier model for the hardest 10% of workloads - and more… GLM 4.7 hits 96% on Tau² Bench and 86% on GPQA Diamond. At 1,500 tokens/sec on Cerebras, it's 20x faster than closed-source alternatives on GPUs.

Cerebras

633,658 Aufrufe • vor 5 Monaten

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!
3:40

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

Andrew Ng

1,224,283 Aufrufe • vor 1 Jahr