GLM-5.1: Z.AI's 1M-token context model
Z.AI's flagship. Up to a 1M-token context window. Strong for whole-codebase or whole-knowledge-base agents at well below Sonnet pricing.
1M tokens · Text / Code · Prompt cache
Okou no longer runs GLM-5.1. This page is kept as a reference for its specs, pricing and benchmarks. For the same kind of work, use GPT 5.6 Luna.
See GPT 5.6 LunaGLM-5.1 is the long-context specialist in the lineup, with up to 1M tokens of input. Reach for it when the prompt is genuinely huge: a whole repository at once, several hundred documents in a single research run. Independent leaderboards consistently rank it in the top tier of open-weight models for long-context work.
Vendor list price is $1.40 / $4.40 per 1M tokens, well under half of Sonnet 4.6 at the vendor level, and the API is Anthropic-compatible so Claude-style agents drop in without a rewrite. Reach for Sonnet or Opus when English reasoning depth matters more than context size, and for Kimi K2.7 Code when latency dominates.
What is GLM-5.1?
Z.AI / Zhipu AI's flagship general-purpose model.
GLM-5.1 is the flagship of Zhipu AI's GLM series, distributed via Z.AI. It's a reasoning model with strong general capability and an unusually large context window. Up to 1M tokens, several times larger than the Anthropic and Moonshot defaults at the same price tier.
What's notable about GLM-5.1
Headline architecture and capability features.
GLM-5.1 exposes an up-to-1M-token context window (the largest in the Built-in lineup) through an Anthropic-compatible API surface, so Claude-style agents drop in unchanged. The upstream supports prompt caching at api.z.ai.
Specs at a glance
GLM-5.1 benchmarks
Independent reviews place GLM-5.1 in the top tier of open-weight models for long-context tasks. Numbers shift weekly on third-party leaderboards. We deliberately don't pin exact percentages here.
GLM-5.1 pricing
Provider list price, per 1M tokens.
How GLM-5.1 behaves in practice
Observed behaviour from production agent runs.
Long-context recall
GLM-5.1's 1M-token window is genuinely usable. It maintains coherence well past the 200K boundary that limits the Anthropic family on the older 200K models. Useful for whole-repo or whole-doc-corpus agents.
Reasoning
Solid general reasoning. Below Sonnet 4.6 on the hardest English-language multi-tool routing, but the gap is small relative to the cost difference.
Best agent tasks for GLM-5.1
The whole-repo refactor that fits in one prompt
Drop a 500K-token mid-sized codebase into a single GLM-5.1 call and ask for a cross-file rename, an architectural review, or a security pass. Models with smaller windows force you to chunk the repo and stitch results together, which is where bugs creep in. GLM-5.1 keeps every file in working memory and references the right paths in its output.
The research run over hundreds of documents
Wikis, RFCs, contracts, last year's support tickets — load the whole pile at once and ask for cross-document patterns. The cost-per-run stays manageable because of the low vendor price, which is what makes this kind of "read everything, summarise once" workflow actually affordable in production rather than a one-off science project.
When to skip GLM-5.1
Skip GLM-5.1 on the hardest English-language reasoning where Sonnet 4.6 or Opus 4.7 still leads, and on latency-critical chat replies where Kimi K2.7 Code is much faster.
GLM-5.1 vs other models
GLM-5.1 vs Kimi K2.7 Code
Both are long-context options at similar credit cost (×0.4 vs ×0.3). Kimi has stronger long-context recall in our internal evaluation; GLM-5.1 wins on raw context size (1M vs 256K). Pick Kimi for very long transcripts; pick GLM-5.1 when you need to stuff a whole codebase into one prompt.
GLM-5.1 vs Claude Sonnet 4.6
Sonnet 4.6 (×1) leads on tool-routing accuracy and English-language reasoning. GLM-5.1 (×0.4) leads on context window and is the right pick when cost or context size dominates the decision.
GLM-5.1 vs DeepSeek V4 Pro
DeepSeek V4 Pro (×0.1) is cheaper and benchmarks higher on Code Arena per third-party reviews. GLM-5.1 still wins on context size. Pick DeepSeek for cost-sensitive standard-context work; pick GLM-5.1 when context size is the constraint.
Bottom line: should you use GLM-5.1?
Pick GLM-5.1 when context size is the constraint. For everything else, DeepSeek V4 Pro is cheaper and Sonnet 4.6 routes tools more reliably.
Availability of GLM-5.1 on Okou
GLM-5.1 has been removed from the Okou lineup, so it can no longer be selected in chat or in a workflow, and it is not available with your own API key. GPT 5.6 Luna covers the same cost-saving tier.