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http://Z.ai releases GLM-5.1, a 754B-parameter model that it says outperforms GPT-5.4 and Claude Opus 4.6 on SWE-bench Pro, available under an MIT license (@carlfranzen / VentureBeat) https://ventureb
I spent the night testing open-source coding models against Claude Opus in production. Same codebase. Same tasks. Real API calls, real file edits, real bugs. Tested: Arcee Trinity-Large-Thinking, http
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)
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...
Let’s deep dive into GLM model improvement by @Zai_org over the past 3 generations: 5.1, 5 and 4.7. GLM-5 was an improvement over 4.7 in similar ways, but 5.1 appears as a more rounded model with a fe
The chart says GLM-5.1 scored 54.9 on coding benchmarks. Three points behind Claude Opus 4.6. Interesting but not the story. The story is what trained it. Zero Nvidia GPUs. 100,000 Huawei Ascend 910B
To run GLM-5.1 locally (744B params, 40B active MoE), full precision needs ~1.65TB disk + enterprise hardware like 8x H200/B200 GPUs. Minimum practical setup: Unsloth 2-bit GGUF quant (~220-236GB). Fi