The verdict
GLM-5.2 appears in 1 AI-ranked category — best position #2 for open-weight llm.
Positioning brief — for the GLM-5.2 team
Why the models put GLM-5.2 at #2 for open-weight llm
- frontier-grade coding and reasoning GPT · Grok“frontier-grade coding, reasoning, tool use”
- long-horizon agentic workflows GPT · Grok · Gemini“highly optimized for long-horizon agentic workflows”
- multi-step tool-use GPT · Gemini“multi-step tool-use”
- permissive MIT license Grok · Gemini“MIT license enables broad use for building production apps”
What the models credit DeepSeek-V4 (#1) with — and don’t credit GLM-5.2
- dramatically reduced KV cache usage Gemini“dramatically reducing KV cache usage”
- low active parameters Grok“MoE with low active params”
- proven scalable self-hosting value Grok“proven self-hosting value for scalable app backends”
What would move the rank — the models’ fix lines, unified
- multi-GPU self-hosting demands GPT · Gemini · Grok“practical self-hosting a multi-GPU or datacenter undertaking”
- less mature community ecosystem Gemini“less mature community library ecosystem outside Chinese developer circles”
- less emphasis on multimodality Grok“less emphasis on multimodality”
Restructured from verbatim model output · nothing invented · every quote machine-verified
Best overall balance of frontier-grade coding, reasoning, tool use, long-horizon agent work, and low-cost hosted access; narrowly leads DeepSeek-V4-Pro for application development.
Grok Leads open-weight models on key agentic coding and long-horizon benchmarks like SWE-Bench Pro and Terminal-Bench (strong real-world software engineering performance); large MoE with excellent reasoning (e.g., top GPQA); MIT license enables broad use for building production apps.
Gemini A 744B MoE released under a permissive MIT license in mid-2026, highly optimized for long-horizon agentic workflows, multi-step tool-use, and 1M-token context operations.
Where GLM-5.2 falls short, per the models
- GPT Its roughly 753B-weight footprint makes practical self-hosting a multi-GPU or datacenter undertaking.
- Gemini Requires significant memory for self-hosting and suffers from a less mature community library ecosystem outside Chinese developer circles.
- Grok High resource demands for full inference (multi-GPU needed for best performance); less emphasis on multimodality.
Top alternatives per the models: DeepSeek-V4 · Qwen3 · Llama 4 · DeepSeek-V3.2
Head-to-head — how the models call it
Watch GLM-5.2
Boards re-poll weekly and the models change their minds. One short email only when GLM-5.2's standing moves — a rank change, a rival overtaking, or new reasoning from the models. Nothing otherwise.
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GLM-5.2 ranks #2 for best open-weight llm by AI-model consensus. Put the badge in your README, docs or site — it updates automatically as the models re-rank.
[](https://modelsagree.com/best/best-open-weight-llm?utm_source=badge&utm_medium=embed&utm_campaign=badge-glm-5-2)<a href="https://modelsagree.com/best/best-open-weight-llm?utm_source=badge&utm_medium=embed&utm_campaign=badge-glm-5-2"><img src="https://modelsagree.com/badge/glm-5-2.svg" alt="GLM-5.2 — ranked #2 for Best open-weight LLM by AI models on ModelsAgree" height="28"></a>Rankings are computed from what the models answer, re-polled on demand · raw reasoning shown verbatim · methodology