Tasks and inputs
zai-org/GLM-5.2 is listed for Text generation. It accepts text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Hugging Face repository for Text generation.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
zai-org/GLM-5.2 is a Hugging Face repository returned by the public Text generation task feed. Its recorded download count is 2,180,509 and it has 4,795 likes when the repository snapshot was collected. Popularity is useful for discovery, but it is not a performance ranking or a guarantee of suitability.
This record is categorized for Text generation. A task category describes the intended machine-learning problem; it does not prove that every version, checkpoint, quantization, or deployment method produces the same quality. Teams should read the model card and test representative inputs before choosing it.
The public repository lists transformers as its library metadata. Its recorded tags include transformers, safetensors, glm_moe_dsa, text-generation, conversational, en, zh, arxiv:2602.15763. These source details are retained so readers can trace this directory entry back to the repository instead of relying on copied descriptions.
Use inputs that resemble deployment traffic, including difficult and out-of-domain cases. Compare output correctness, the response format, latency and memory requirements with a simple baseline under the same conditions.
Explore zai-org models and the text generation collection. Use the comparison tool to inspect a second candidate.
Compare the model on the work you need to complete.
zai-org/GLM-5.2 is listed for Text generation. It accepts text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 1M context and 131.07K maximum output. The listed route charges $1.40 input and $4.40 output per million tokens. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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