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herdr unlocks so much use cases for multi agent + human fun in the terminal! kimi k3 getting mogged by gpt 5.6 sol every time in chess lol the vision: a full arcade for agents to slack off and message board to comment on the games as they happen!...

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徐樂 xule

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52,481 Aufrufe • vor 13 Tagen •via X (Twitter)

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Kimi K3 beating Fable and Sol on price and quality. Command Code's internal flappy bench results are in. Really impressed with the results. For Kimi K3 we set the gameplay to hard while Fable 5 and GPT-5.6 Sol were set to easier. Cost breakdown: • Kimi K3: $0.024 •Fable 5: $0.42 •GPT-5.6 Sol: $0.15 Ranking based on DX & features: •Kimi K3: 8/10 •Fable 5: 7.5/10 • GPT-5.6 Sol: 7/10 GPT 5.6 Sol max can definitely go on longer and wins the game overall, but that's something different. Grok 4.5 beats GPT 5.6 Sol on that, lol.Mm-hmm.
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Kimi K3 beating Fable and Sol on price and quality. Command Code's internal flappy bench results are in. Really impressed with the results. For Kimi K3 we set the gameplay to hard while Fable 5 and GPT-5.6 Sol were set to easier. Cost breakdown: • Kimi K3: $0.024 •Fable 5: $0.42 •GPT-5.6 Sol: $0.15 Ranking based on DX & features: •Kimi K3: 8/10 •Fable 5: 7.5/10 • GPT-5.6 Sol: 7/10 GPT 5.6 Sol max can definitely go on longer and wins the game overall, but that's something different. Grok 4.5 beats GPT 5.6 Sol on that, lol.Mm-hmm.

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255,237 Aufrufe • vor 1 Monat

Kimi K3 vs GPT-5.6 Sol — same game build, a fraction of the cost. Kimi K3 just 3-shotted a Fallout Vault-Tec FPS clone. $2.48 in API usage. The same token count runs $5.34 on GPT-5.6 Sol. a full playable FPS for the price of a coffee. K3 dropped this week: 2.8 trillion parameters, open weights July 27. I broke down exactly how to build with it — full Kimi K3 guide below.
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Kimi K3 vs GPT-5.6 Sol — same game build, a fraction of the cost. Kimi K3 just 3-shotted a Fallout Vault-Tec FPS clone. $2.48 in API usage. The same token count runs $5.34 on GPT-5.6 Sol. a full playable FPS for the price of a coffee. K3 dropped this week: 2.8 trillion parameters, open weights July 27. I broke down exactly how to build with it — full Kimi K3 guide below.

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It worked!! Kimi k3 Oauth is now wired directly into codex. The Kimi k3 model is insane but their app is not. So I figure a better way to use k3 by hooking my sub straight into codex instead. K3 now sits in the model picker next to Sol 5.6. Same subscription i was already paying for, no api key, just have to do OAuth in Kimi Code. Links down below 👇
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It worked!! Kimi k3 Oauth is now wired directly into codex. The Kimi k3 model is insane but their app is not. So I figure a better way to use k3 by hooking my sub straight into codex instead. K3 now sits in the model picker next to Sol 5.6. Same subscription i was already paying for, no api key, just have to do OAuth in Kimi Code. Links down below 👇

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A swarm of GPT 5.6 Sol agents spent over 40 hours optimizing a Kimi K3-like model from 65 to 406 tok/s. This animation follows their collaboration as they discover operator fusions, transform the execution graph, and develop new kernel algorithms.
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A swarm of GPT 5.6 Sol agents spent over 40 hours optimizing a Kimi K3-like model from 65 to 406 tok/s. This animation follows their collaboration as they discover operator fusions, transform the execution graph, and develop new kernel algorithms.

Xenova

75,371 Aufrufe • vor 1 Monat

Codexers: Multi-agent v2 now supports GPT-5.6 Luna. You can use Luna Max as a native sub-agent in Codex and benefit from the incredible price/performance ratio. 'sol-advisor' just shipped support for this. Free and open-source 👇
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Codexers: Multi-agent v2 now supports GPT-5.6 Luna. You can use Luna Max as a native sub-agent in Codex and benefit from the incredible price/performance ratio. 'sol-advisor' just shipped support for this. Free and open-source 👇

Dan McAteer

92,826 Aufrufe • vor 7 Tagen

Qwen 3.8 will be benchmaxxed slop second to fable 5 is such a hype statement , its not even close to kimi k3 and GPT-5.6 sol you can test it yourself on the qwen chat website currently available > token hungry > not that good as advertised , will test more The best part of kimi was that in blog they themselves wrote its not comparable to fable 5 and sol 5.6 in bunch of user experience stuff We need more truth like this in our industry , other than that i will run my vision test
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Qwen 3.8 will be benchmaxxed slop second to fable 5 is such a hype statement , its not even close to kimi k3 and GPT-5.6 sol you can test it yourself on the qwen chat website currently available > token hungry > not that good as advertised , will test more The best part of kimi was that in blog they themselves wrote its not comparable to fable 5 and sol 5.6 in bunch of user experience stuff We need more truth like this in our industry , other than that i will run my vision test

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wow... GPT 5.6 Sol Passed the Replit Benchmark. In one prompt 5.6 on Codex created a full Replit clone with DB, Sandboxes, and an agent that builds and edits full web apps. Only Fable and GPT 5.6 have passed this benchmark. 5.6 is much better at designing iOS apps than 5.5 as well.
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wow... GPT 5.6 Sol Passed the Replit Benchmark. In one prompt 5.6 on Codex created a full Replit clone with DB, Sandboxes, and an agent that builds and edits full web apps. Only Fable and GPT 5.6 have passed this benchmark. 5.6 is much better at designing iOS apps than 5.5 as well.

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Use AI in every app on Mac, enriched by context from the app you're in. Generate replies in Gmail, summarise your Slack, or let GPT fill out the contents of a web form! Try it now for the best (and cheapest) way to use GPT-4!
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Use AI in every app on Mac, enriched by context from the app you're in. Generate replies in Gmail, summarise your Slack, or let GPT fill out the contents of a web form! Try it now for the best (and cheapest) way to use GPT-4!

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announcing slack operator: a simple web agent powered by openai's new computer-use model i'm dropping the source code below so you can use this for your next web agent project want to try a live version? leave a comment and i'll add you to our slack!
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announcing slack operator: a simple web agent powered by openai's new computer-use model i'm dropping the source code below so you can use this for your next web agent project want to try a live version? leave a comment and i'll add you to our slack!

Paul Klein IV

97,272 Aufrufe • vor 1 Jahr

🚨 Deepseek V4 pro GA is being tested to few users > this is the output on the same prompt that was used for kimi k3 and GPT sol 5.6 in the quoted video > The details are solid , addition of tents , campfire and everything this model looks promising
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🚨 Deepseek V4 pro GA is being tested to few users > this is the output on the same prompt that was used for kimi k3 and GPT sol 5.6 in the quoted video > The details are solid , addition of tents , campfire and everything this model looks promising

Chetaslua

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qwen 3.8 max vs deepseek v4 flash 0731 vs kimi k3 vs gpt 5.6 sol – on rubik's cube and chess four frontier models built a rubik's cube stand and solved it, then built a chess board and played claude opus 5 on it the setup: Nous Research's hermes agent cli on OpenRouter tasks: 1. cube – build a 3d rubik's cube with a cli and a Three.js viewer, then solve an identical scrambled position on your own stand 2. chess – build a 3d chess stand, then play white against claude opus 5 as black, live, one move at a time. no engine, no solver, no opening book on either side. stockfish depth 14 grades every chess ply afterwards; neither player sees the score models: DeepSeek v4 flash 0731, OpenAI gpt-5.6 sol, Kimi.ai kimi k3, Qwen qwen 3.8 max gpt-5.6 sol and deepseek v4 flash solved their cubes – sol in 24 moves and seventeen seconds, deepseek in 32. qwen and kimi never got there, giving up at 96 and 207 moves then all four built chess stands and played white against claude opus 5 on them, and all four resigned: deepseek on move 13, sol on 19, kimi on 21, qwen holding out longest at 29 - build time, both stands #1 gpt-5.6 sol – 16m 43s #2 deepseek v4 flash – 97m 39s #3 kimi k3 – 166m 09s #4 qwen 3.8 max – 215m 08s - build attempts before a working stand #1 gpt-5.6 sol – 3 #2 qwen 3.8 max – 4 #3 kimi k3 – 4 #4 deepseek v4 flash – 5 - total tokens #1 gpt-5.6 sol – 6,713,754 #2 qwen 3.8 max – 17,272,507 #3 kimi k3 – 22,427,504 #4 deepseek v4 flash – 27,417,442 - total price #1 deepseek v4 flash – $0.557 #2 gpt-5.6 sol – $6.319 #3 qwen 3.8 max – $10.270 #4 kimi k3 – $16.667 observations: • deepseek v4 flash is the cheapest model here by a margin nobody else is near, and it got there while being the least efficient of the four. it burned 27.4m tokens – more than anyone, 5m more than kimi – and still finished both benchmarks for $0.557. that is $0.02 per million tokens against kimi's $0.74. it also needed the most passes to produce working stands, five, and that did not matter: all five deepseek passes together cost a thirtieth of kimi's two • so what deepseek cannot do is get it right the first time. what it can do is get it right the fifth time, for half a dollar. that is a different thing to be buying – not a good first draft, but the option to keep asking • gpt-5.6 sol is the opposite profile and the strongest of the four on pure efficiency. 16m 43s to build both stands, 6.7m tokens, three passes – under 40% of the next lowest token count and a quarter of deepseek's, on an eighth of qwen's clock. it also solved the cube fastest of anyone, 24 moves in seventeen seconds. sol is what you reach for when you want the answer now and can absorb $0.94 per million • sol's weakness is in what it does not check. its chess viewer deleted the capturing piece instead of the captured one, so pieces disappeared off the board mid-game – a defect the fifty-cent deepseek stand did not have. fast and terse turns out to be the same dial as fast and unverified • qwen 3.8 max is not the cheap open-weights option it gets treated as. $10.270 across the two benchmarks, second most expensive of the four, 18x deepseek, and by a distance the slowest – 215 minutes of build time, nearly thirteen times sol's. what the money buys is judgment: it played eighteen moves without a single error worth a hundredth of a pawn, then made exactly one bad move in the whole game, and averaged 44.6 centipawns lost across the longest game any of the four managed. it also could not solve a rubik's cube in 96 tries • kimi k3 is the one line with no reading that flatters it. most expensive at $16.667, last on the cube at 207 moves, last at chess at 478 centipawns lost per move. it is also the model that verified hardest – on the cube it wrote its own integrity check instead of trusting its output. that makes the result worse rather than better: the checking was real, and the reasoning underneath it still was not follow thehype. for 24/7 ai news, analysis and breakdowns
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qwen 3.8 max vs deepseek v4 flash 0731 vs kimi k3 vs gpt 5.6 sol – on rubik's cube and chess four frontier models built a rubik's cube stand and solved it, then built a chess board and played claude opus 5 on it the setup: Nous Research's hermes agent cli on OpenRouter tasks: 1. cube – build a 3d rubik's cube with a cli and a Three.js viewer, then solve an identical scrambled position on your own stand 2. chess – build a 3d chess stand, then play white against claude opus 5 as black, live, one move at a time. no engine, no solver, no opening book on either side. stockfish depth 14 grades every chess ply afterwards; neither player sees the score models: DeepSeek v4 flash 0731, OpenAI gpt-5.6 sol, Kimi.ai kimi k3, Qwen qwen 3.8 max gpt-5.6 sol and deepseek v4 flash solved their cubes – sol in 24 moves and seventeen seconds, deepseek in 32. qwen and kimi never got there, giving up at 96 and 207 moves then all four built chess stands and played white against claude opus 5 on them, and all four resigned: deepseek on move 13, sol on 19, kimi on 21, qwen holding out longest at 29 - build time, both stands #1 gpt-5.6 sol – 16m 43s #2 deepseek v4 flash – 97m 39s #3 kimi k3 – 166m 09s #4 qwen 3.8 max – 215m 08s - build attempts before a working stand #1 gpt-5.6 sol – 3 #2 qwen 3.8 max – 4 #3 kimi k3 – 4 #4 deepseek v4 flash – 5 - total tokens #1 gpt-5.6 sol – 6,713,754 #2 qwen 3.8 max – 17,272,507 #3 kimi k3 – 22,427,504 #4 deepseek v4 flash – 27,417,442 - total price #1 deepseek v4 flash – $0.557 #2 gpt-5.6 sol – $6.319 #3 qwen 3.8 max – $10.270 #4 kimi k3 – $16.667 observations: • deepseek v4 flash is the cheapest model here by a margin nobody else is near, and it got there while being the least efficient of the four. it burned 27.4m tokens – more than anyone, 5m more than kimi – and still finished both benchmarks for $0.557. that is $0.02 per million tokens against kimi's $0.74. it also needed the most passes to produce working stands, five, and that did not matter: all five deepseek passes together cost a thirtieth of kimi's two • so what deepseek cannot do is get it right the first time. what it can do is get it right the fifth time, for half a dollar. that is a different thing to be buying – not a good first draft, but the option to keep asking • gpt-5.6 sol is the opposite profile and the strongest of the four on pure efficiency. 16m 43s to build both stands, 6.7m tokens, three passes – under 40% of the next lowest token count and a quarter of deepseek's, on an eighth of qwen's clock. it also solved the cube fastest of anyone, 24 moves in seventeen seconds. sol is what you reach for when you want the answer now and can absorb $0.94 per million • sol's weakness is in what it does not check. its chess viewer deleted the capturing piece instead of the captured one, so pieces disappeared off the board mid-game – a defect the fifty-cent deepseek stand did not have. fast and terse turns out to be the same dial as fast and unverified • qwen 3.8 max is not the cheap open-weights option it gets treated as. $10.270 across the two benchmarks, second most expensive of the four, 18x deepseek, and by a distance the slowest – 215 minutes of build time, nearly thirteen times sol's. what the money buys is judgment: it played eighteen moves without a single error worth a hundredth of a pawn, then made exactly one bad move in the whole game, and averaged 44.6 centipawns lost across the longest game any of the four managed. it also could not solve a rubik's cube in 96 tries • kimi k3 is the one line with no reading that flatters it. most expensive at $16.667, last on the cube at 207 moves, last at chess at 478 centipawns lost per move. it is also the model that verified hardest – on the cube it wrote its own integrity check instead of trusting its output. that makes the result worse rather than better: the checking was real, and the reasoning underneath it still was not follow thehype. for 24/7 ai news, analysis and breakdowns

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Ultrafast mode for GPT-5.6 Sol is now in limited preview, powered by Cerebras. We gave OpenAI's GPT-5.6 Sol the same prompt on Ultrafast and Standard: build a financial terminal-style dashboard for analysts. Ultrafast: 1 min 50 seconds Standard: 12 min 20 seconds Same result, nearly 7x faster.
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Ultrafast mode for GPT-5.6 Sol is now in limited preview, powered by Cerebras. We gave OpenAI's GPT-5.6 Sol the same prompt on Ultrafast and Standard: build a financial terminal-style dashboard for analysts. Ultrafast: 1 min 50 seconds Standard: 12 min 20 seconds Same result, nearly 7x faster.

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Use Grok to dispatch tasks to GPT-5.6-Sol. Grok is fast and smart, so it's great at breaking work into chunks and dispatching them. Then let GPT-5.6-Sol Xhigh handle the deep thinking. Once it's done, have everything report back to Grok for summarization and the final answer. All with the built-in Orchestration in Orca ADE.
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Use Grok to dispatch tasks to GPT-5.6-Sol. Grok is fast and smart, so it's great at breaking work into chunks and dispatching them. Then let GPT-5.6-Sol Xhigh handle the deep thinking. Once it's done, have everything report back to Grok for summarization and the final answer. All with the built-in Orchestration in Orca ADE.

jinjingliang

27,983 Aufrufe • vor 1 Monat

CLAUDE OPUS 5, GPT-5.6 SOL AND KIMI K3 ARE ALL SITTING IN A FREE TIER WITH 7 MILLION TOKENS A DAY • NaraRouter, the gateway > 7M tokens every 24 hours, no card, no subscription: > Claude Opus 5, Sonnet 5 and Fable 5, GPT-5.6 Sol, Terra and Luna, Kimi K3, Qwen3.8 Max, GLM 5.2, DeepSeek V4 Pro and MiniMax M3. > Anthropic-compatible /v1/messages alongside the OpenAI route, so it drops into Claude Code without a proxy. • the multiplier is the real price list > Each model drains the allowance at its own rate -- Sol at 4x, DeepSeek V4 Pro at 3x, Kimi K3 at 1.5x. > Opus 5, Sonnet 5, Fable 5 and Luna carry no multiplier at all. So 7M on Luna is 7M, and 7M on Sol is closer to 1.75M -> pick by the badge, not by the name. Sign up with Google, copy the key once, point your base url at and you are running ↓
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CLAUDE OPUS 5, GPT-5.6 SOL AND KIMI K3 ARE ALL SITTING IN A FREE TIER WITH 7 MILLION TOKENS A DAY • NaraRouter, the gateway > 7M tokens every 24 hours, no card, no subscription: > Claude Opus 5, Sonnet 5 and Fable 5, GPT-5.6 Sol, Terra and Luna, Kimi K3, Qwen3.8 Max, GLM 5.2, DeepSeek V4 Pro and MiniMax M3. > Anthropic-compatible /v1/messages alongside the OpenAI route, so it drops into Claude Code without a proxy. • the multiplier is the real price list > Each model drains the allowance at its own rate -- Sol at 4x, DeepSeek V4 Pro at 3x, Kimi K3 at 1.5x. > Opus 5, Sonnet 5, Fable 5 and Luna carry no multiplier at all. So 7M on Luna is 7M, and 7M on Sol is closer to 1.75M -> pick by the badge, not by the name. Sign up with Google, copy the key once, point your base url at and you are running ↓

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Previewing Ultrafast mode for OpenAI's GPT 5.6 Sol, powered by Cerebras. GPT-5.6 Sol Ultrafast generates responses at up to 750 tokens per second. That's the full, GPT-5.6-Sol model -- up to 14× faster than the same model on Standard processing. It speedran Humanity’s Last Exam in 11h 11m, nearly 7× faster than Claude Fable 5 with comparable accuracy.

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Shopify stores with GPT-5.6 Sol 🤯 5.6 Sol lets you copy proven sections from the world's biggest Shopify brands and add them to your theme in seconds Drop a GIF in the comments, and I'll send you one of the highest-converting sections generated by Sol You need to follow me first so I can message you
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33,775 Aufrufe • vor 1 Monat

GPT 5.6 Sol in Codex just one-shot this... It made a mascot for my app, then generated ~30 variations of the mascot representing my app’s top use cases. I was so blown away, I had to share it:
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GPT 5.6 Sol in Codex just one-shot this... It made a mascot for my app, then generated ~30 variations of the mascot representing my app’s top use cases. I was so blown away, I had to share it:

Jarrod Watts

17,632 Aufrufe • vor 1 Monat

Introducing multi-agent orchestration in Oz, with support for Claude Code, Codex and the Warp Agent. Use /orchestrate to delegate complex tasks across a team of agents, locally or in the cloud.
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1,198,715 Aufrufe • vor 3 Monaten