Thinking Machines Releases Inkling-Small, Outperforms Larger Model
Thinking Machines Lab's second open-weight model needs a quarter of its predecessor's active parameters yet edges past it on reasoning and coding benchmarks.
Read more →Every AI News story tagged with both Open-Weight Models and AI Research — the two topics side by side, updated as new articles publish.
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Thinking Machines Lab's second open-weight model needs a quarter of its predecessor's active parameters yet edges past it on reasoning and coding benchmarks.
Read more →China's Moonshot AI released Kimi K3, a 2.8-trillion-parameter open model with a 1-million-token context window — a system the company calls the world's first open 3-trillion-class AI model.
Read more →PrismML has released Bonsai 27B, a 27-billion-parameter open-weight model compressed to under 4GB, small enough to run natively on a phone while keeping most of its reasoning ability.
Read more →Mira Murati's startup released Inkling, a 975-billion-parameter open-weight model built for developers to fine-tune and adapt, rather than to top leaderboards.
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DeepSeek is the Chinese AI lab whose cheaply trained, open-weight models triggered Nvidia's biggest one-day stock drop and reshaped how the industry talks about AI costs.
Read more →GLM is the open-weight AI model family from Chinese lab Zhipu AI (Z.ai) — free to download and self-host, and competitive with top US models at a fraction of the API cost.
Read more →Z.ai has released GLM-5.2, a 744-billion-parameter open-weight model that matches GPT-5.5 on key benchmarks and trails Claude Opus 4.8 narrowly — trained entirely on Huawei silicon with no Nvidia hardware.
Read more →Mistral's new open-source model for Lean 4 fully saturates the miniF2F theorem benchmark, solves 87% of graduate-level math tests, and found five previously unknown bugs in production code — at roughly $4 per proof versus $300 for competing systems.
Read more →Chinese technology company Meituan has released LongCat-2.0, a 1.6-trillion-parameter coding model trained entirely on domestic Chinese chips, under the MIT License — the first frontier-class open-source model built without Western semiconductors.
Read more →Open-weight AI models release their trained parameters publicly so anyone can download, run, or fine-tune them — unlike closed models such as GPT-4 or Gemini, which are accessible only through paid APIs. Here is what that difference means in practice.
Read more →GLM-5.2, released on June 16 by Beijing startup Z.ai, sits alongside Claude Opus 4.8 and GPT-5.5 on coding benchmarks while carrying an API price roughly one-sixth that of closed US models.
Read more →Alibaba's Qwen team released a language world model that learns to predict agent environment states across seven domains, offering a new approach to training AI agents without live systems.
Read more →Liquid AI released LFM2.5-230M, a 230-million-parameter open-weight model that runs AI agent tasks at 213 tokens per second on a phone CPU and 42 tokens per second on a Raspberry Pi — without a cloud connection.
Read more →Chinese lab Zhipu AI has open-sourced GLM-5.2, a 753-billion-parameter model that outperforms GPT-5.5 on software engineering benchmarks while costing roughly one-sixth as much.
Read more →Alibaba's Qwen team has released Qwen-AgentWorld, a family of open-source language world models that predict how digital environments respond to AI agent actions, with its 397B variant outscoring GPT-5.4 on the new AgentWorldBench benchmark.
Read more →The Google DeepMind spinoff signed a three-year, $6.3 billion computing contract with SpaceX's Colossus data center, giving it the GPU scale needed to challenge closed AI giants with open-weight models.
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