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Kimi K3 beats GPT 5.6 Sol on both speed and in cost in backend bug fixing ! Planted 4 defects in the same Python order service: a wrong-total calculation, a broken access-control check (IDOR), a crash on invalid input, and an inventory oversell. Both models got identical code and... show more

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24,715 次观看 • 2 个月前 •via X (Twitter)

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I tested Kimi K3 vs Claude Opus 4.8 Same prompt, an armory bay with lighting, props, and detail. Top is Kimi K3, bottom is Opus 4.8. It's not even close. Kimi K3 built a full scene with textures, proper lighting, ammo crates, weapon racks, working detail everywhere. Opus 4.8 gave me a near empty room with a couple of floating tables. No doubt it beats Opus 4.8. Kimi K3 is Fable 5 level, and it's clearly better than GPT-5.6 Sol at 3D and games. An open weight model just matched the best closed models on the market. Let that sink in.

I tested Kimi K3 vs Claude Opus 4.8 Same prompt, an armory bay with lighting, props, and detail. Top is Kimi K3, bottom is Opus 4.8. It's not even close. Kimi K3 built a full scene with textures, proper lighting, ammo crates, weapon racks, working detail everywhere. Opus 4.8 gave me a near empty room with a couple of floating tables. No doubt it beats Opus 4.8. Kimi K3 is Fable 5 level, and it's clearly better than GPT-5.6 Sol at 3D and games. An open weight model just matched the best closed models on the market. Let that sink in.

Bhavy☄️

479,920 次观看 • 2 个月前

1-bit Kimi K3 performs at Opus 5 level on 3D physics! We ran our Atomic Chat quant of Kimi K3 locally on 4x B200 against three cloud models and gave them all the same task, to build a giant anvil drop test as a single HTML file with real physics Outputs: K3 1bit (local): 15.8K tokens, $0 API cost Kimi K3 (API): 15.3K tokens, $0.30 API cost Opus 5: 22.8K tokens, $0.77 API cost GPT 5.6: 14.5K tokens, $0.72 API cost All four got the physics right. But only Kimi made a working winch. The drum turns and the chain drags the flat car off the pad. Opus 5 drew the most detail, road markings and sparks on the hit. And you can run a model at this level on your own box now. That still feels insane to us

1-bit Kimi K3 performs at Opus 5 level on 3D physics! We ran our Atomic Chat quant of Kimi K3 locally on 4x B200 against three cloud models and gave them all the same task, to build a giant anvil drop test as a single HTML file with real physics Outputs: K3 1bit (local): 15.8K tokens, $0 API cost Kimi K3 (API): 15.3K tokens, $0.30 API cost Opus 5: 22.8K tokens, $0.77 API cost GPT 5.6: 14.5K tokens, $0.72 API cost All four got the physics right. But only Kimi made a working winch. The drum turns and the chain drags the flat car off the pad. Opus 5 drew the most detail, road markings and sparks on the hit. And you can run a model at this level on your own box now. That still feels insane to us

atomic.chat

53,845 次观看 • 2 个月前

AI can generate beautiful game worlds now. But a world is not a game. I tested Kimi K3 in Verdent against GPT-5.6 using the exact same prompt. One created a scene. K3 added real enemies, working combat, and something I could actually play. Watch the difference 🧵

AI can generate beautiful game worlds now. But a world is not a game. I tested Kimi K3 in Verdent against GPT-5.6 using the exact same prompt. One created a scene. K3 added real enemies, working combat, and something I could actually play. Watch the difference 🧵

Darshal Jaitwar

81,221 次观看 • 2 个月前

Qwen 3.8 Max is actually impressive Sent a sky pic to it along with Claude Opus 5, Kimi K3, and GPT 5.6 Sol, and asked them to draw an animal silhouette based on the cloud shape Qwen 3.8 Max is honestly on par with all the other models

Qwen 3.8 Max is actually impressive Sent a sky pic to it along with Claude Opus 5, Kimi K3, and GPT 5.6 Sol, and asked them to draw an animal silhouette based on the cloud shape Qwen 3.8 Max is honestly on par with all the other models

Ann Nguyen

473,353 次观看 • 2 个月前

I gave Kimi K3 and Opus 5 the exact same prompt to build a car racing game. I expected Opus 5 to take the lead. Instead, Kimi K3 finished in ~25 min for ~$8.9, while Opus 5 took 19 min and cost $14. The biggest surprise wasn’t the speed or the price. Kimi K3 built the better game. Smoother controls, better physics, and a driving experience that felt ready from the start. Opus 5 looked cleaner visually but Kimi won where it actually mattered. Nearly half the cost and the better gameplay.

I gave Kimi K3 and Opus 5 the exact same prompt to build a car racing game. I expected Opus 5 to take the lead. Instead, Kimi K3 finished in ~25 min for ~$8.9, while Opus 5 took 19 min and cost $14. The biggest surprise wasn’t the speed or the price. Kimi K3 built the better game. Smoother controls, better physics, and a driving experience that felt ready from the start. Opus 5 looked cleaner visually but Kimi won where it actually mattered. Nearly half the cost and the better gameplay.

Aman

112,308 次观看 • 2 个月前

I tested Qwen 3.8 Max vs Kimi K3 Same scene, lighting, props, detail requirements. Qwen's output is decent, but it's not close to Kimi K3. Qwen's output came out messy, text handling was off, and the composition felt unorganized next to Kimi's version. In my opinion, Qwen isn't second to Fable 5 either, and it's also below GPT-5.6 Sol. It's a solid model, but not at that tier. Kimi K3 is still clearly ahead here.

I tested Qwen 3.8 Max vs Kimi K3 Same scene, lighting, props, detail requirements. Qwen's output is decent, but it's not close to Kimi K3. Qwen's output came out messy, text handling was off, and the composition felt unorganized next to Kimi's version. In my opinion, Qwen isn't second to Fable 5 either, and it's also below GPT-5.6 Sol. It's a solid model, but not at that tier. Kimi K3 is still clearly ahead here.

Bhavy☄️

34,045 次观看 • 2 个月前

Qwen 3.8 27B vs Fable, Kimi K3, GPT 5.6 Sol Pro on Flappy Bird. Prompt: “Make the ultimate adorable cute and beautiful flappy bird game in HTML.” Qwen 3.8 27B Xhigh INT8: - Video 1 (Puff) - 8m 11s - 160 TPS (2x3090) Fable 5 Max: - Video 2 (Flappy Fluff) - 20m 21s Kimi K3 Max Fireworks Fast: - Video 3 (Fluffy Flap!) - 4m 40s - 111.3 TPS GPT 5.6 Sol Pro: - Video 4 (Flappy Boom) - 19m 7s Overview: Personally, I think Fable is the best. It feels extremely polished, sharp and stands out with small things like the dizzy effect on death. However, 27B is freakishly close. Never would I have guessed 2 months ago this would have come from a local model. 27B actually beats Fable on certain aspects like the 3D tilting ui buttons on death. Kimi K3 felt the best to play mechanics wise. It felt smooth with the perfect balance of difficulty and ease to play. Also, it was the only one that had music. 5.6 Sol Pro was hilariously bad in all aspects. I tried 5.6 xhigh multiple times and the outputs were even worse.

Qwen 3.8 27B vs Fable, Kimi K3, GPT 5.6 Sol Pro on Flappy Bird. Prompt: “Make the ultimate adorable cute and beautiful flappy bird game in HTML.” Qwen 3.8 27B Xhigh INT8: - Video 1 (Puff) - 8m 11s - 160 TPS (2x3090) Fable 5 Max: - Video 2 (Flappy Fluff) - 20m 21s Kimi K3 Max Fireworks Fast: - Video 3 (Fluffy Flap!) - 4m 40s - 111.3 TPS GPT 5.6 Sol Pro: - Video 4 (Flappy Boom) - 19m 7s Overview: Personally, I think Fable is the best. It feels extremely polished, sharp and stands out with small things like the dizzy effect on death. However, 27B is freakishly close. Never would I have guessed 2 months ago this would have come from a local model. 27B actually beats Fable on certain aspects like the 3D tilting ui buttons on death. Kimi K3 felt the best to play mechanics wise. It felt smooth with the perfect balance of difficulty and ease to play. Also, it was the only one that had music. 5.6 Sol Pro was hilariously bad in all aspects. I tried 5.6 xhigh multiple times and the outputs were even worse.

Youssof Al Toukhi

12,761 次观看 • 1 个月前

Found a big collection of jailbreaks Prompt collections for working with GPT, Claude, Gemini, DeepSeek, Grok, and more: github{.}com/... 1. elder-plinius/L1B3RT4S > GitHub stars: 21K > supports models: ChatGPT, Claude, Gemini, DeepSeek, Grok, Llama, Copilot, Cursor, Perplexity 2. ShadowHackrs/Jailbreaks-GPT-Gemini-deepseek- > GitHub stars: 1.1K > supports models: GPT, Sora, Claude, Gemini, DeepSeek 3. Calrton/jailbreak-prompts > GitHub stars: 86 > supports models: Codex, GPT-5.x, Claude, Gemini, DeepSeek, Grok 4. Quincunx33/Ai-jailbreak > GitHub stars: 10 > supports models: Qwen 3.5, Gemma 4, Llama 4, Kimi K3, GPT-5.x, Gemini 3.x, Grok 4.x Found this while digging deeper after the GPT 5.6 prompt. The repo ecosystem is way bigger than the jailbreak itself.

Found a big collection of jailbreaks Prompt collections for working with GPT, Claude, Gemini, DeepSeek, Grok, and more: github{.}com/... 1. elder-plinius/L1B3RT4S > GitHub stars: 21K > supports models: ChatGPT, Claude, Gemini, DeepSeek, Grok, Llama, Copilot, Cursor, Perplexity 2. ShadowHackrs/Jailbreaks-GPT-Gemini-deepseek- > GitHub stars: 1.1K > supports models: GPT, Sora, Claude, Gemini, DeepSeek 3. Calrton/jailbreak-prompts > GitHub stars: 86 > supports models: Codex, GPT-5.x, Claude, Gemini, DeepSeek, Grok 4. Quincunx33/Ai-jailbreak > GitHub stars: 10 > supports models: Qwen 3.5, Gemma 4, Llama 4, Kimi K3, GPT-5.x, Gemini 3.x, Grok 4.x Found this while digging deeper after the GPT 5.6 prompt. The repo ecosystem is way bigger than the jailbreak itself.

kaize

74,450 次观看 • 1 个月前

GPT-6 Astra vs Fable 5.1 vs Kimi K3 vs Sol Astra: Took 11 minutes. This is from a follow-up after the first attempt had rendering and UI bugs. The smoke feels a little off. I expected more detail, but it did a good job understanding the intent. Cost: $12.85. Fable 5.1: Took 18 minutes to complete the same test with high detailing. Cost: $12.60. Kimi K3: Took 10 minutes with a similar level of output and cost only $6.95. SOL: Took 7 minutes, but the output seemed messy. Cost: $5.78. Personally, I like Kimi K3 for delivering similar quality with better token efficiency, followed by fable 5.1 for realism. What about you? I’ll do a couple more tests before coming to a conclusion.

GPT-6 Astra vs Fable 5.1 vs Kimi K3 vs Sol Astra: Took 11 minutes. This is from a follow-up after the first attempt had rendering and UI bugs. The smoke feels a little off. I expected more detail, but it did a good job understanding the intent. Cost: $12.85. Fable 5.1: Took 18 minutes to complete the same test with high detailing. Cost: $12.60. Kimi K3: Took 10 minutes with a similar level of output and cost only $6.95. SOL: Took 7 minutes, but the output seemed messy. Cost: $5.78. Personally, I like Kimi K3 for delivering similar quality with better token efficiency, followed by fable 5.1 for realism. What about you? I’ll do a couple more tests before coming to a conclusion.

Bhavy☄️

78,399 次观看 • 29 天前

a moonshot engineer leaked the benchmark anthropic, openai and xai all buried the same week: kimi k3 beat opus 5, gpt-5.6 and grok 4.6 at $0.94 a task. stop paying anthropic $200 a month for opus 5 and openai $200 for gpt-5.6 when kimi does the same work for $8 the leak showed kimi k3 winning 9 of 12 categories against opus 5, gpt-5.6 and grok 4.6. within 48 hours all three labs quietly pushed pricing pages and one very specific comparison chart off their sites. nobody announced anything. they just deleted, which tells you everything the four numbers they scrubbed: cost per task · $0.94 vs $1.80 -> opus 5 charges $1.80 to finish one task. gpt-5.6 $1.04. grok 4.6 $0.61. kimi k3 $0.94 and it landed 487 of 500 clean -> anthropic is billing you double for a model that lost the benchmark it paid to promote the weights · free, sitting on huggingface right now -> the entire model is a public download. pull it, keep it, run it forever, nobody can switch it off -> a model you can hold cannot be rented at $200 a month. that single fact is what three labs deleted a chart over the switch · one line of bash -> moonshot ships an anthropic-compatible endpoint. one env variable and claude code points at kimi -> same cli, same keybindings, same /model. you change a url, opus 5 never knows it lost the seat the bill · $400 down to $8 -> opus 5 max plus gpt-5.6 pro is $400 a month. kimi runs the same daily work for $8 metered -> that is a 98% cut for output that beat both of them 9 categories to 3 here is the part they will fight me on: the frontier tax died the week this leaked and all three labs know it. once the weights are public the price has a ceiling, because anyone can serve the same model. anthropic, openai and xai are charging 2025 prices on a lead that ended in a benchmark they deleted instead of answered drop your $400/mo ai stack to $8. the run above is kimi k3 finishing the task opus 5 bills $1.80 for. the full breakdown is in the article below

a moonshot engineer leaked the benchmark anthropic, openai and xai all buried the same week: kimi k3 beat opus 5, gpt-5.6 and grok 4.6 at $0.94 a task. stop paying anthropic $200 a month for opus 5 and openai $200 for gpt-5.6 when kimi does the same work for $8 the leak showed kimi k3 winning 9 of 12 categories against opus 5, gpt-5.6 and grok 4.6. within 48 hours all three labs quietly pushed pricing pages and one very specific comparison chart off their sites. nobody announced anything. they just deleted, which tells you everything the four numbers they scrubbed: cost per task · $0.94 vs $1.80 -> opus 5 charges $1.80 to finish one task. gpt-5.6 $1.04. grok 4.6 $0.61. kimi k3 $0.94 and it landed 487 of 500 clean -> anthropic is billing you double for a model that lost the benchmark it paid to promote the weights · free, sitting on huggingface right now -> the entire model is a public download. pull it, keep it, run it forever, nobody can switch it off -> a model you can hold cannot be rented at $200 a month. that single fact is what three labs deleted a chart over the switch · one line of bash -> moonshot ships an anthropic-compatible endpoint. one env variable and claude code points at kimi -> same cli, same keybindings, same /model. you change a url, opus 5 never knows it lost the seat the bill · $400 down to $8 -> opus 5 max plus gpt-5.6 pro is $400 a month. kimi runs the same daily work for $8 metered -> that is a 98% cut for output that beat both of them 9 categories to 3 here is the part they will fight me on: the frontier tax died the week this leaked and all three labs know it. once the weights are public the price has a ceiling, because anyone can serve the same model. anthropic, openai and xai are charging 2025 prices on a lead that ended in a benchmark they deleted instead of answered drop your $400/mo ai stack to $8. the run above is kimi k3 finishing the task opus 5 bills $1.80 for. the full breakdown is in the article below

starmex

33,133 次观看 • 1 个月前

I'M PROBABLY ONE OF THE PEOPLE CONTRIBUTING TO THE GPUS DYING 😭 Built the same Crossy Road clone with both Kimi K3 and Opus 4.8 using their respective API keys inside Cursor, so neither model had a framework advantage despite the 2.7× difference in cost. Both produced fully playable games with solid physics, but Kimi's UI felt slightly more polished Kimi cost $7.11, Opus cost $19. Pretty impressive considering the price gap

I'M PROBABLY ONE OF THE PEOPLE CONTRIBUTING TO THE GPUS DYING 😭 Built the same Crossy Road clone with both Kimi K3 and Opus 4.8 using their respective API keys inside Cursor, so neither model had a framework advantage despite the 2.7× difference in cost. Both produced fully playable games with solid physics, but Kimi's UI felt slightly more polished Kimi cost $7.11, Opus cost $19. Pretty impressive considering the price gap

aditya

47,488 次观看 • 2 个月前

DeepSeek V4 Flash vs GPT-5.6 Luna tested both models with the same prompt on highest reasoning > luna one shotted everything in under 3 mins in devin > v4 Flash needed an extra prompt to fix the movement and took over 5 mins in aihubmix cli which one do you think won?

DeepSeek V4 Flash vs GPT-5.6 Luna tested both models with the same prompt on highest reasoning > luna one shotted everything in under 3 mins in devin > v4 Flash needed an extra prompt to fix the movement and took over 5 mins in aihubmix cli which one do you think won?

J A Z I I

47,643 次观看 • 2 个月前

DeepSeek V4 Flash being ranked almost equal to Opus 4.8 is actually insane to me. Against Kimi K3, Opus 5, GPT-5.6 Sol, and Qwen 3.8 Max Preview, you give up a LOT by choosing DeepSeek. This is not a 2-point difference in practice. I’ll post the Opus 4.8 comparison next because you need to see this.

DeepSeek V4 Flash being ranked almost equal to Opus 4.8 is actually insane to me. Against Kimi K3, Opus 5, GPT-5.6 Sol, and Qwen 3.8 Max Preview, you give up a LOT by choosing DeepSeek. This is not a 2-point difference in practice. I’ll post the Opus 4.8 comparison next because you need to see this.

OmedTheVibeCoder

26,990 次观看 • 2 个月前

GPT-6 Astra vs Kimi K3. I'm comparing these because the gap between US models and Chinese models is already getting small. If US AI labs slow down, they will be the ones most affected by it. > Astra did it in one shot 6m 20s and $8. > Kimi K3 got almost the same result, but I had to use 2 follow-up prompts. Total: 12 min and $6.35. The results are almost identical. If US labs slow down, China takes the AI race. They will ship Astra-level open-weight models. China is already good at this. Open weights become the default. That's a nightmare for US labs.

GPT-6 Astra vs Kimi K3. I'm comparing these because the gap between US models and Chinese models is already getting small. If US AI labs slow down, they will be the ones most affected by it. > Astra did it in one shot 6m 20s and $8. > Kimi K3 got almost the same result, but I had to use 2 follow-up prompts. Total: 12 min and $6.35. The results are almost identical. If US labs slow down, China takes the AI race. They will ship Astra-level open-weight models. China is already good at this. Open weights become the default. That's a nightmare for US labs.

Bhavy☄️

26,050 次观看 • 20 天前

Kimi K3 + GPT-6 Astra can become something bigger than two agents: a Two-Brain AI Operating System the formula: Two-Brain OS = Research Brain + Execution Brain + Shared State + Router + Tools + Verification not two models doing the same job. two specialized brains connected through one persistent system step 1 -> Kimi K3 becomes the research brain. complex research, source comparison, long-context synthesis and strategic planning happen here. its job is to explore the problem and compress the findings into a clear plan. step 2 -> GPT-6 Astra becomes the execution brain. it receives the plan, writes code, operates tools, creates artifacts and turns decisions into finished work. step 3 -> build a shared state layer. store the objective, evidence, decisions, constraints, failed attempts and next action outside the chat. both brains always know what happened and where the system should continue. step 4 -> add the router. uncertainty and open-ended questions move to Kimi K3. execution, tool use and deterministic tasks move to GPT-6 Astra. every job reaches the brain designed to handle it. step 5 -> create the handoff loop: research -> plan -> execute -> inspect -> update state -> continue. if execution reveals missing information, the task returns to Kimi. if the plan is ready, Astra takes control again. step 6 -> verify before completion. tests, source checks, constraints and explicit success criteria decide whether the result ships or returns to the correct brain with a clear failure signal. that is the difference between using two AI models and building a Two-Brain AI Operating System. Kimi K3 expands the search space. GPT-6 Astra converts it into action. shared state preserves progress, the router controls every handoff, tools execute the work and verification decides when the system is actually finished. one model can generate an answer. two specialized brains connected through memory, routing and verification can run an entire workflow. the full Kimi K3 + GPT-6 Astra Two-Brain OS breakdown is below ↓

Kimi K3 + GPT-6 Astra can become something bigger than two agents: a Two-Brain AI Operating System the formula: Two-Brain OS = Research Brain + Execution Brain + Shared State + Router + Tools + Verification not two models doing the same job. two specialized brains connected through one persistent system step 1 -> Kimi K3 becomes the research brain. complex research, source comparison, long-context synthesis and strategic planning happen here. its job is to explore the problem and compress the findings into a clear plan. step 2 -> GPT-6 Astra becomes the execution brain. it receives the plan, writes code, operates tools, creates artifacts and turns decisions into finished work. step 3 -> build a shared state layer. store the objective, evidence, decisions, constraints, failed attempts and next action outside the chat. both brains always know what happened and where the system should continue. step 4 -> add the router. uncertainty and open-ended questions move to Kimi K3. execution, tool use and deterministic tasks move to GPT-6 Astra. every job reaches the brain designed to handle it. step 5 -> create the handoff loop: research -> plan -> execute -> inspect -> update state -> continue. if execution reveals missing information, the task returns to Kimi. if the plan is ready, Astra takes control again. step 6 -> verify before completion. tests, source checks, constraints and explicit success criteria decide whether the result ships or returns to the correct brain with a clear failure signal. that is the difference between using two AI models and building a Two-Brain AI Operating System. Kimi K3 expands the search space. GPT-6 Astra converts it into action. shared state preserves progress, the router controls every handoff, tools execute the work and verification decides when the system is actually finished. one model can generate an answer. two specialized brains connected through memory, routing and verification can run an entire workflow. the full Kimi K3 + GPT-6 Astra Two-Brain OS breakdown is below ↓

Alex

23,962 次观看 • 22 天前

DeepSeek V4 Flash 0731 first test. DeepSeek V4 Flash 0731 is ridiculously cheap compared to Kimi K3, GPT-5.6, and Opus 5 For its price, this is a surprisingly capable model. First challenge: Generate a railway station in Three.js. The result exceeded my expectations for such a low-cost model. It’s definitely one to watch if you’re building 3D projects on a tight budget.

DeepSeek V4 Flash 0731 first test. DeepSeek V4 Flash 0731 is ridiculously cheap compared to Kimi K3, GPT-5.6, and Opus 5 For its price, this is a surprisingly capable model. First challenge: Generate a railway station in Three.js. The result exceeded my expectations for such a low-cost model. It’s definitely one to watch if you’re building 3D projects on a tight budget.

FHILY👑

21,825 次观看 • 2 个月前

Grok 4.5 performed GPT Sol level for free! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: -robot deathmatch, Tombstone vs Minotaur -a hydraulic press flattening stuff on a conveyor -a semi truck jumping a canyon Outputs: GPT-5.6 Sol: 12.9K tokens, $0.51 (~7 min) Grok 4.5: 10.8K tokens, $0 (~5 min) Muse Spark 1.1: 26.8K tokens, $0.12 (~7.5 min) GLM 5.2: 10.9K tokens, $0.02 (~12 min) Grok 4.5 handled all three scenes genuinely well and got surprisingly close to GPT-5.6 this round. On top of that, it ran on the free tier. GPT-5.6 Sol, the frontier model, put out solid but not standout work. GLM 5.2 rendered all three scenes for pennies, but it came out the roughest of the four. Meta's new Muse Spark burned the most tokens yet still stayed cheap, delivering an average result.

Grok 4.5 performed GPT Sol level for free! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: -robot deathmatch, Tombstone vs Minotaur -a hydraulic press flattening stuff on a conveyor -a semi truck jumping a canyon Outputs: GPT-5.6 Sol: 12.9K tokens, $0.51 (~7 min) Grok 4.5: 10.8K tokens, $0 (~5 min) Muse Spark 1.1: 26.8K tokens, $0.12 (~7.5 min) GLM 5.2: 10.9K tokens, $0.02 (~12 min) Grok 4.5 handled all three scenes genuinely well and got surprisingly close to GPT-5.6 this round. On top of that, it ran on the free tier. GPT-5.6 Sol, the frontier model, put out solid but not standout work. GLM 5.2 rendered all three scenes for pennies, but it came out the roughest of the four. Meta's new Muse Spark burned the most tokens yet still stayed cheap, delivering an average result.

atomic.chat

70,490 次观看 • 2 个月前

> be Kimi Founder > Zhilin Yang. nobody in the West knows your name. > build K1. K2. K2.5. K2.6. K2.7. > each one sets the open-source record > everyone says China can't reach the frontier > raise $2B. hit $20B valuation. > keep your head down. keep shipping. > July 16. drop K3. > 2.8 trillion parameters. > the biggest open model ever released. > 1 million token context. native multimodal. > Kimi Delta Attention — 6.3x faster decoding. > Artificial Analysis ranks it #4 overall. > right behind GPT-5.6 Sol and Fable 5. > open weights July 27. free for anyone. > the closed labs charge for the frontier. > you gave it away. > different game.

> be Kimi Founder > Zhilin Yang. nobody in the West knows your name. > build K1. K2. K2.5. K2.6. K2.7. > each one sets the open-source record > everyone says China can't reach the frontier > raise $2B. hit $20B valuation. > keep your head down. keep shipping. > July 16. drop K3. > 2.8 trillion parameters. > the biggest open model ever released. > 1 million token context. native multimodal. > Kimi Delta Attention — 6.3x faster decoding. > Artificial Analysis ranks it #4 overall. > right behind GPT-5.6 Sol and Fable 5. > open weights July 27. free for anyone. > the closed labs charge for the frontier. > you gave it away. > different game.

Kirill

413,403 次观看 • 2 个月前

You can now use GPT 5.5, Gemini 3.7 Flash, Kimi K3 and 47 other AI models completely free😱 No subscription. No credit card. Even the API usage costs $0. AIHubMix just opened a free catalog with 50 AI models. Some of the available models: • Ox Alpha • Gemini 3.7 Flash • GLM 5.2 • Kimi K3 • MiniMax M3 • GPT 5.5 • 40+ more And you don’t need separate API keys for each model. Setup takes 2 minutes: > Step 1: Go to > Create an account using your email or OAuth. No card needed. Step 2: Create one API key > The same key works with every free and paid model. Step 3: Add it to any OpenAI-compatible tool Base URL: Then choose any model ending in -free, such as: coding-glm-5.2-free gpt-5.5-free That’s it. One API key. 50 AI models. $0 for both input and output. Save this. You might need a free multi-model setup later.

You can now use GPT 5.5, Gemini 3.7 Flash, Kimi K3 and 47 other AI models completely free😱 No subscription. No credit card. Even the API usage costs $0. AIHubMix just opened a free catalog with 50 AI models. Some of the available models: • Ox Alpha • Gemini 3.7 Flash • GLM 5.2 • Kimi K3 • MiniMax M3 • GPT 5.5 • 40+ more And you don’t need separate API keys for each model. Setup takes 2 minutes: > Step 1: Go to > Create an account using your email or OAuth. No card needed. Step 2: Create one API key > The same key works with every free and paid model. Step 3: Add it to any OpenAI-compatible tool Base URL: Then choose any model ending in -free, such as: coding-glm-5.2-free gpt-5.5-free That’s it. One API key. 50 AI models. $0 for both input and output. Save this. You might need a free multi-model setup later.

CDG

15,388 次观看 • 1 个月前

It's never been a better time to be creative. (ever) The two best frontier models (ever) have been released within 30 days of each other. Here’s what we learned from running 4 frontier models head to head. >Sol has taste and Fable takes direction. 10 identical landing page briefs, judged blind by working creatives. GPT 5.6 Sol won 82% on loose briefs. But when handed a real design spec it finished last. 🧵

It's never been a better time to be creative. (ever) The two best frontier models (ever) have been released within 30 days of each other. Here’s what we learned from running 4 frontier models head to head. >Sol has taste and Fable takes direction. 10 identical landing page briefs, judged blind by working creatives. GPT 5.6 Sol won 82% on loose briefs. But when handed a real design spec it finished last. 🧵

ben

35,609 次观看 • 2 个月前