Model ID
internlm/Atria-Dawn-Preview
Capabilities
Atria Dawn Preview
Atria Dawn Preview is an agentic model built on the 744B-parameter GLM-5.2 foundation. It uses a 78-layer sparse Mixture-of-Experts architecture with 256 routed experts and 8 activated per token, combining DeepSeek Sparse Attention (DSA) with dense and sparse MLP layers. The model supports a 1M-token context window and 64 attention heads, with 64 key-value heads and one next-token prediction layer. It targets scientific automation, software creation, research, document generation, cybersecurity, and long-horizon tasks requiring iterative tool use and execution.
About this model
Atria Dawn Preview is an agentic model built on the 744B-parameter GLM-5.2 foundation. It uses a 78-layer sparse Mixture-of-Experts architecture with 256 routed experts and 8 activated per token, combining DeepSeek Sparse Attention (DSA) with dense and sparse MLP layers. The model supports a 1M-token context window and 64 attention heads, with 64 key-value heads and one next-token prediction layer. It targets scientific automation, software creation, research, document generation, cybersecurity, and long-horizon tasks requiring iterative tool use and execution.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (internlm/Atria-Dawn-Preview). Released under MIT. Further reading: Paper
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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