Model ID
zai-org/GLM-5.2
Capabilities
GLM 5.2
GLM 5.2 is an advanced Mixture-of-Experts language model designed for long-horizon reasoning, large-scale coding, and million-token context processing. It features a 78-layer architecture with 6,144 hidden size and 64 attention heads, activating 8 experts per token across 256 routed experts and a shared expert. The model incorporates IndexShare sparse attention to improve long-context efficiency and an enhanced multi-token prediction layer for faster speculative decoding. Supporting up to a 1M token context window, it is optimized for complex reasoning, extended coding workflows, and sustained long-context tasks.
About this model
GLM 5.2 is an advanced Mixture-of-Experts language model designed for long-horizon reasoning, large-scale coding, and million-token context processing. It features a 78-layer architecture with 6,144 hidden size and 64 attention heads, activating 8 experts per token across 256 routed experts and a shared expert. The model incorporates IndexShare sparse attention to improve long-context efficiency and an enhanced multi-token prediction layer for faster speculative decoding. Supporting up to a 1M token context window, it is optimized for complex reasoning, extended coding workflows, and sustained long-context tasks.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (zai-org/GLM-5.2). Released under MIT. Further reading: Blog
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Hardware
MI355X
2,304 GB
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on MI355X · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
AMD Instinct MI355X
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