GLM-5.2
Open-weight 744B-parameter frontier model from Zhipu AI built for coding, reasoning, and long-horizon agentic work, with a 1M-token context and an MIT license.
Updated 2026-06-27
Overview
GLM-5.2 is Zhipu AI's latest open-weight large language model, a 744-billion-parameter system tuned for coding, multi-step reasoning, and long-horizon agentic tasks. Released June 13-14, 2026 under an MIT license, it ships with a 1M-token context window and is positioned to compete directly with closed frontier models from OpenAI, Anthropic, and Google — except you can download the weights and run them yourself.
The headline isn't just the benchmark numbers (Zhipu claims results competitive with, and on some coding and agentic evaluations ahead of, top proprietary models). It's the licensing. MIT is about as permissive as open weights get: no usage caps, no commercial restrictions, no revocable API terms. For teams that want a frontier-class coding model they fully control — fine-tuning, on-prem deployment, no data leaving their infrastructure — that combination is rare. Most "open" models at this tier carry restrictive community licenses; GLM-5.2 doesn't.
It's built for the agentic era specifically: long context plus tool-use orientation means it's aimed at coding agents that plan, call tools, and run for many turns rather than one-shot completions. You can try it free through the Z.ai chat interface, get 20M free tokens on API signup, or self-host the weights. The catch is the same one every massive open model carries — running 744B parameters locally is a serious hardware commitment, so for most users the hosted API or chat UI is the realistic path.
Key features
744B Open Weights
A 744-billion-parameter frontier model released as downloadable open weights under MIT, so teams can self-host, fine-tune, and deploy on their own infrastructure with no API lock-in or usage restrictions.
1M-Token Context
A one-million-token context window lets it ingest entire codebases, long document sets, or extended agent histories in a single pass — useful for whole-repo reasoning and long-running agent sessions.
Agentic Coding Focus
Tuned for long-horizon, multi-turn tasks where the model plans, calls tools, and iterates over many steps, rather than just one-shot completions — the workload that powers modern coding agents.
Free Access On Signup
Try it free in the Z.ai chat interface, claim 20M free tokens on API signup, or download the weights at no cost — multiple low-friction ways to evaluate before committing to a paid plan.
Pricing
Free tier: Free chat access plus 20M free tokens on API signup, and open weights available to download and self-host under MIT.
| Plan | Price | What's included |
|---|---|---|
| Free / Open Weights | $0 | Free access via the Z.ai chat interface, 20M free tokens on API signup, and full model weights downloadable under the MIT license for self-hosting and fine-tuning. |
| API (Pay-as-you-go) | Check website for current pricing | Token-based API access for production use beyond the free allotment, billed per input/output token. |
| GLM Coding Plan | Check website for current pricing | Subscription tier aimed at developers using GLM inside coding agents and IDE integrations, with higher usage allowances than the free tier. |
Free access via the Z.ai chat interface, 20M free tokens on API signup, and full model weights downloadable under the MIT license for self-hosting and fine-tuning.
Token-based API access for production use beyond the free allotment, billed per input/output token.
Subscription tier aimed at developers using GLM inside coding agents and IDE integrations, with higher usage allowances than the free tier.
Pros & cons
Pros
- ✓MIT-licensed open weights — full commercial use, self-hosting, and fine-tuning with no revocable API terms
- ✓1M-token context handles whole codebases and long agent histories in one pass
- ✓Benchmark results competitive with top closed frontier models, especially on coding and agentic tasks
- ✓Genuinely free to start: chat UI, 20M signup tokens, or download the weights
- ✓Strong fit for coding agents thanks to its long-horizon, tool-use orientation
Cons
- ×At 744B parameters, self-hosting demands serious GPU hardware — out of reach for most individual developers
- ×Vendor-published benchmarks need independent verification; real-world coding performance may vary from the claims
- ×Hosted API and coding-plan pricing isn't transparently listed, so budgeting requires checking the site
- ×As a model from Zhipu AI, some enterprises face data-residency or procurement constraints around China-based providers
How it compares
| Tool | Best for | Pricing | Score |
|---|---|---|---|
| GLM-5.2 | — | Free 20M tokens on signup + open weights; paid API & coding plans (check site) | 8.7/10 |
| Cursor vs Cursor → | — | Freemium | 9.5/10 |
| GPT-5.5 vs GPT-5.5 → | — | API: $5/$30 per 1M tokens (in/out). ChatGPT Plus $20/mo, Pro $200/mo | 9.4/10 |
| Windsurf vs Windsurf → | — | Freemium | 9.1/10 |
Compare head-to-head
Related reading
GLM-5.2: Z.ai Open Model Tops Coding Benchmarks
Z.ai's GLM-5.2 open-weights model beats GPT-5.5 on long-horizon coding benchmarks at a fraction of the cost, per VentureBeat.
Gov and Big Labs Get Frontier AI First. We Don't.
The most capable AI now reaches a few labs and the government first, then trickles to the public in guardrailed form. Why that precedent matters.
GPT-5.6 Sol, Terra, Luna: OpenAI's Limited Preview
OpenAI's GPT-5.6 family ships as a gated preview after a US government request. Here's what Sol, Terra, and Luna actually are.
Ready to try GLM-5.2?
Head to the official site to start with GLM-5.2 — pricing and plans are listed above.
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