What GLM-5.1 Is
GLM-5.1 is Z.ai's (formerly Zhipu AI) flagship open-weight model (released April 2026): a 754B-parameter MoE (~40B active), MIT-licensed, with a ~200K context window and 128K max output. Its defining trait is stamina — it's built to run a single engineering task autonomously for up to 8 hours, planning, executing, and self-correcting toward complete, deliverable results. Z.ai calls it the shift "from vibe coding to agentic engineering."
Benchmarks
GLM-5.1 is one of the strongest open-weight coding models: it scored 58.4% on SWE-Bench Pro and was independently placed 3rd on Code Arena (~1530 Elo) — the first major independent verification of Z.ai's coding claims. Agentic scores are strong too (BrowseComp 68%, τ³-Bench ~70%). Notably, it was trained entirely on Huawei Ascend chips.
Pricing
Roughly $1.40 input / $4.40 output per 1M tokens (some providers as low as ~$0.97/$3.04), with cache reads around $0.26. As an MIT-licensed open-weight model, you can also self-host it if you have the hardware. On LinkModel it runs behind one key alongside Claude, GPT, Gemini, DeepSeek, and Kimi, up to 30% below official.
When to Use It
- Long-horizon coding agents — its 8-hour autonomous stamina is purpose-built for multi-hour engineering runs where the model must hold context and standards throughout.
- Self-hosting for data sovereignty — MIT license + open weights make on-prem viable.
- Agentic tool use — strong BrowseComp/MCP scores for browser and tool workflows.
When Not To
- Cheap high-volume text → DeepSeek V4 Flash is far cheaper.
- Top correctness per attempt → Claude Opus 4.8.
- Multimodal input → GLM-5.1 is text-focused; use Kimi K2.6 or Gemini for images.
How to Call It
GLM is OpenAI-compatible. Through a gateway:
curl -X POST https://api.linkmodel.ai/v1/chat/completions \
-H "Authorization: Bearer $LINKMODEL_API_KEY" -H "Content-Type: application/json" \
-d '{ "model": "glm-5.1", "messages": [{"role":"user","content":"Refactor this module and add tests: ..."}] }'Confirm the exact chat endpoint and schema in the docs. For long agent runs, keep a stable prompt prefix to capture the cache-read rate.
Cost Control
- Cache the repo map / system prompt → cache reads ~$0.26 vs ~$1.40 fresh.
- Route down → use GLM-5.1 for the long/hard engineering tasks, a cheaper model for boilerplate. See best coding LLM API and how to reduce AI API costs.
Bottom Line
GLM-5.1 is a top open-weight choice for long-horizon, autonomous coding and for teams that want the option to self-host. For cheap bulk text, DeepSeek; for top correctness, Claude; for multimodal, Kimi. Compare in best LLM API.
Start free with a $1 credit and point a coding agent at it.
