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After testing all recents opensource model kimi k2.6 is best base model > thats why composer is that good one example of its greatness ,all other open model fails this rubix test

Chetaslua

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17,845 views • 3 months ago •via X (Twitter)

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Kimi K2.6 is godly in terms of webdev and still SOTA chinese model 😼 > best in deep SWE bench even after launches of multiple models from different chinese labs Look at the watery feel one shotted it < using custom harness - 4 kimi in parallel just like grok >

Kimi K2.6 is godly in terms of webdev and still SOTA chinese model 😼 > best in deep SWE bench even after launches of multiple models from different chinese labs Look at the watery feel one shotted it < using custom harness - 4 kimi in parallel just like grok >

Chetaslua

117,033 views • 3 months ago

Ox Alpha : flash multimodal This is one shot loop i ask it to make a loop of pelican riding bike and open his phone where the same gif is looping This is benefit of multimodality and now we will have good opensource model with it

Ox Alpha : flash multimodal This is one shot loop i ask it to make a loop of pelican riding bike and open his phone where the same gif is looping This is benefit of multimodality and now we will have good opensource model with it

Chetaslua

13,947 views • 27 days ago

GLM 5.2 is first chinese model that made 3d watch without any major mistakes 🤯 Z.ai you guys cooked very hard with this model , now only thing that we need is the big fat model , tell us the time when we can expect This is one of the hardest thing to one shot

GLM 5.2 is first chinese model that made 3d watch without any major mistakes 🤯 Z.ai you guys cooked very hard with this model , now only thing that we need is the big fat model , tell us the time when we can expect This is one of the hardest thing to one shot

Chetaslua

294,253 views • 3 months ago

Kimi K3 absolutely mogs every open source model this is on par , head on head all case i tried in coding with fable , i feel weird to write , but sometimes it output better quality than fable too I don't know how to comprehend this , i have lots of test and comparison 😼

Kimi K3 absolutely mogs every open source model this is on par , head on head all case i tried in coding with fable , i feel weird to write , but sometimes it output better quality than fable too I don't know how to comprehend this , i have lots of test and comparison 😼

Chetaslua

131,209 views • 2 months ago

Eric my man i dont know what you guys done with the pro model its faster and feels so good , here is Three.js contruction of monica apartment the level of detail was not present in any other model till today

Eric my man i dont know what you guys done with the pro model its faster and feels so good , here is Three.js contruction of monica apartment the level of detail was not present in any other model till today

Chetaslua

28,441 views • 5 months ago

🚨 The Sims one shotted by GPT-5.6 Pro this is without codex or any coding harness , one shot entire game with logic in 48 minutes, all in one .html file. cc : Mirochill for the test roon when we can have big model taste and personality ? like after GPT 5 its so robotic

🚨 The Sims one shotted by GPT-5.6 Pro this is without codex or any coding harness , one shot entire game with logic in 48 minutes, all in one .html file. cc : Mirochill for the test roon when we can have big model taste and personality ? like after GPT 5 its so robotic

Chetaslua

144,849 views • 3 months ago

Opus 5 is great model but we need to see performance on stuff that are not famous It fails hard on my 3d elephant test , dont get me wrong this is best try than any other llm till date but we are far from the basic 3d world understanding Jagged intelligence , they need to work on multimodality

Opus 5 is great model but we need to see performance on stuff that are not famous It fails hard on my 3d elephant test , dont get me wrong this is best try than any other llm till date but we are far from the basic 3d world understanding Jagged intelligence , they need to work on multimodality

Chetaslua

26,838 views • 1 month ago

🚨 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

🚨 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

172,573 views • 2 months ago

all i know is that there is only one of Yasmin Wijnaldum! a MODEL.

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all i know is that there is only one of Yasmin Wijnaldum! a MODEL.

b✨

42,920 views • 11 months ago

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. :-)

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

40,593 views • 3 months ago

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

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

Chetaslua

127,047 views • 2 months ago

THIS IS THE IMPORTANCE OF PUPPETEERING! I rigged this model in under 5 hours with no vbridger included~ its all about your body and facial movements to help the model feel more alive >w<

THIS IS THE IMPORTANCE OF PUPPETEERING! I rigged this model in under 5 hours with no vbridger included~ its all about your body and facial movements to help the model feel more alive >w<

c r y

73,300 views • 10 months ago

🚨Gemini 3.0 Pro - One shotted i asked it for retro nintendo sims with games and no external assets used , it takes 1 min to output no other model have this level of consistency Prompt and Proof of one shot in Thread and this is not the best shot , there is one more cooking with slightly different prompt

🚨Gemini 3.0 Pro - One shotted i asked it for retro nintendo sims with games and no external assets used , it takes 1 min to output no other model have this level of consistency Prompt and Proof of one shot in Thread and this is not the best shot , there is one more cooking with slightly different prompt

Chetaslua

184,281 views • 11 months ago

📢VTubers📢 Your model is NOT a one-size-fits-all! Calibrating a model to fit you is one of the most important FREE WAYS to instantly IMPROVE YOUR VTUBER MODEL!

📢VTubers📢 Your model is NOT a one-size-fits-all! Calibrating a model to fit you is one of the most important FREE WAYS to instantly IMPROVE YOUR VTUBER MODEL!

Yomi Quinnley🧪💙【SVA】

20,133 views • 6 months ago

Super Mario one shotted by Gemini Pro 3.2/5 this is one the best visuals and gameplay by any model , consistency with the old design is the key Google Gemini cooked this so well

Super Mario one shotted by Gemini Pro 3.2/5 this is one the best visuals and gameplay by any model , consistency with the old design is the key Google Gemini cooked this so well

Chetaslua

15,036 views • 4 months ago

Cybercab testing this morning at Giga Texas … I saw several testing runs around the factory today, here is a portion of one of these runs. Chase Model 3 is back & LiDAR Model Y cameo too.

Cybercab testing this morning at Giga Texas … I saw several testing runs around the factory today, here is a portion of one of these runs. Chase Model 3 is back & LiDAR Model Y cameo too.

Joe Tegtmeyer 🚀 🤠🛸😎

196,573 views • 1 year ago

The new SpaceX-Cursor model is going to be insane. It is being trained from scratch, unlike previous Composer models, which were built off Kimi. This new model is Elon’s attempt to get back in the AI race, and he might rejoin as the frontrunner. Composer 2.5 is already a world-class model, only losing to models like GPT-5.5, Opus 4.8, and Fable 5. Grok Composer 3, with SpaceX’s massive compute and xAI’s team, could become the best AI model on the planet. Elon is back.

The new SpaceX-Cursor model is going to be insane. It is being trained from scratch, unlike previous Composer models, which were built off Kimi. This new model is Elon’s attempt to get back in the AI race, and he might rejoin as the frontrunner. Composer 2.5 is already a world-class model, only losing to models like GPT-5.5, Opus 4.8, and Fable 5. Grok Composer 3, with SpaceX’s massive compute and xAI’s team, could become the best AI model on the planet. Elon is back.

Ali Romman

119,837 views • 3 months ago

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!

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

110,057 views • 4 months ago