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We partnered with @Zai_org to bring GLM-5.1 to Modal. Free to try as an endpoint for the next month. GLM-5.1 further improves upon GLM-5's c…

We partnered with @Zai_org to bring GLM-5.1 to Modal. Free to try as an endpoint for the next month. GLM-5.1 further improves upon GLM-5's coding abilities and long-horizon effectiveness. Introducing

8 Apr 2026

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A lot of you are asking about the :cloud tag. Here's the deal: GLM-5.1 is a 744B parameter beast. To hit that 54.9 benchmark score without t…

DGX agent

A lot of you are asking about the :cloud tag. Here's the deal: GLM-5.1 is a 744B parameter beast. To hit that 54.9 benchmark score without turning my M4 Mac Mini into a space heater, I run the cloud e

model-releaseszhipu-ai--x

7 Apr 2026

GLM 5.1 is now LIVE in Atomic Chat SOTA for code & chat – now runs locally with TurboQuant Thanks to @zai_org for open-sourcing this frontie…

GLM-5.1 is Z.ai's (zai-org) next-generation open-source flagship model for agentic engineering, achieving state-of-the-art performance on SWE-Bench Pro and significantly outperforming its predecess...

GLM-5.1: Towards Long-Horizon Tasks

model-releasessimon-willison

GLM-5.1: Towards Long-Horizon Tasks Chinese AI lab Z.ai's latest model is a giant 754B parameter 1.51TB (on Hugging Face) MIT-licensed monster - the same size as their previous GLM-5 release, and shar

How can you improve your agentic search pipeline? I just wrote a blog post with @tech_optimist from @lancedb to answer exactly that. TLDR: -…

model-releasesjerry-liu--x

How can you improve your agentic search pipeline? I just wrote a blog post with @tech_optimist from @lancedb to answer exactly that. TLDR: - Parse files and take page-level screenshots with LiteParse,

INCREDIBLE GLM-5.1 weights are now opensource > i’ve had early access to the weights for the past few days > and yeah… this one matters a lo…

INCREDIBLE GLM-5.1 weights are now opensource > i’ve had early access to the weights for the past few days > and yeah… this one matters a lot benchmarks? > SWE-Bench Pro: 58.4 > beats Opus 4.6 (57.3)

Introducing GLM-5.1 for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick co…

AlphaXiv introduced GLM-5.1 as the underlying model powering its research paper understanding features on the alphaXiv platform, enabling users to highlight any section of a paper to ask contextual...

Visually rich documents are especially challenging for agents. Tables, charts, and images often break traditional document pipelines, making…

model-releasesjerry-liu--x

Visually rich documents are especially challenging for agents. Tables, charts, and images often break traditional document pipelines, making complex reasoning difficult📄 So we teamed up with @lancedb