Reasoning Models @reasoningmodels

Introducing a limited preview of GPT-5.6 Sol, our next generation frontier model, as well as GPT-5.6 Terra, a balanced model for efficient, everyday work, and GPT-5.6 Luna, a fast and affordable model for high-volume work. openai.com/index/previewi…

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Reasoning Models @reasoningmodels

4 months ago

Big moves by Meta, Muse Spark looks pretty incredible.

AI at Meta @AIatMeta

4 months ago

Introducing Muse Spark, the first in the Muse family of models developed by Meta Superintelligence Labs. Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration. Muse Spark is available today at

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Reasoning Models @reasoningmodels

4 months ago

@AIatMeta Congrats, major step forward ✨

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Reasoning Models @reasoningmodels

4 months ago

@bindureddy So impressive, Google is cooking 🔥

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Reasoning Models @reasoningmodels

4 months ago

@pmarca Yes

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Reasoning Models @reasoningmodels

4 months ago

This is very interesting

Tim @open_founder

4 months ago

We've been pretty quiet about what we're building. That changes now. Our reasoning framework is currently beating every @OpenAI model on industry standard benchmarks. There are six models in development. SERV-nano just matched GPT-5.4 at 20x lower cost and 3x the speed. The

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Reasoning Models @reasoningmodels

4 months ago

@open_founder @OpenAI Super interesting

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Reasoning Models @reasoningmodels

4 months ago

@iruletheworldmo Yes, sooooo ready for it

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Reasoning Models @reasoningmodels

4 months ago

@iruletheworldmo I feel like it’s probably a solid analogy, just rather than lots of leaks, it’s the biggest leak ever

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Reasoning Models @reasoningmodels

4 months ago

@0xSero What tool are you using to track usage that outputs it like that? Look interesting 👀

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Reasoning Models @reasoningmodels

4 months ago

@SawyerMerritt Pretty incredible, generating $2B/mo, so $24B/year. So 35x annual revenue multiple. This is like a company doing $10M/year in ARR raising at a $350M valuation. Which I think does happen quite a bit, so maybe nothing too unusual here right??

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Reasoning Models @reasoningmodels

4 months ago

@yoonholeee @roshen_nair @qizhengz_alex @Kangwook_Lee @lateinteraction @chelseabfinn Really interesting, need to dig in and really understand this at a deeper level, feels like there could be so many applications to this.

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Reasoning Models @reasoningmodels

4 months ago

This feels like something big.

Yoonho Lee @yoonholeee

4 months ago

How can we autonomously improve LLM harnesses on problems humans are actively working on? Doing so requires solving a hard, long-horizon credit-assignment problem over all prior code, traces, and scores. Announcing Meta-Harness: a method for optimizing harnesses end-to-end

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Reasoning Models @reasoningmodels

4 months ago

If you use Claude, and run out of tokens quickly, this could be why.

Alex Volkov @altryne

4 months ago

PSA: If you've been running out of Claude session quotas on Max tier, you're not alone. Read this. Some insane Redditor reverse engineered the Claude binaries with MITM to find 2 bugs that could have caused cache-invalidation. Tokens that aren't cached are 10x-20x more expensive