GLM-5.2
GLM-5.2
Frontier-class output, an MIT licence, and a million tokens of context. That combination is the story.
Updated
The read
GLM-5.2 is the model that makes the open-versus-closed argument concrete. It trades blows with the closed flagships on coding and general reasoning, it takes a million tokens of context, and the weights are published under MIT with no user threshold and no field-of-use clause. You can run it, tune it, ship it inside a product and never send a byte to anyone. Nothing else in this index offers that much capability on those terms.
Where it shines
- MIT licence with no user-count or field-of-use restrictions
- Competitive with closed flagships on coding benchmarks
- Million-token context on weights you can hold yourself
Worth knowing first
- Serving it well still needs serious GPU capacity
- Some organisations will not deploy a Chinese-origin model regardless of licence
Index score
87.1
Provisional. This score is read from the product's public capability, not from the one-prompt rebuild the fully reviewed entries went through, so treat it as a placing rather than a verdict.
- Rank
- 06 of 53
- Builds
- LLMs
- Category
- Open weights
- Output
- MIT-licensed weights, plus a hosted API
- Pricing
- Free tier
- Best for
- Frontier-class work you need to keep in house
Scores are our own editorial judgement, weighted craft 55, speed 10, control 15 and value 20.
Compare it with
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- 14Mistral Large 3Mistral Large 3ProvisionalEurope's answer, published under Apache 2.0, with a quarter of a million tokens of context.Open weightsFree tier82.9
