Model ID
deepseek-ai/DeepSeek-V4-Flash-0731
Capabilities
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 is a large-scale Mixture-of-Experts model optimized for ultra-long-context reasoning, efficient inference, and enhanced agentic capabilities, with 284B total parameters and approximately 13B activated. It uses 256 routed experts, activating 6 per token, across 43 layers with a 4,096 hidden size and 64 attention heads. Its architecture combines CSA and HCA attention with manifold-constrained hyper-connections and supports a 1M-token context window. It features FP4 expert weights, FP8 quantization, and a speculative decoding module for faster generation.
About this model
DeepSeek V4 Flash 0731 is a large-scale Mixture-of-Experts model optimized for ultra-long-context reasoning, efficient inference, and enhanced agentic capabilities, with 284B total parameters and approximately 13B activated. It uses 256 routed experts, activating 6 per token, across 43 layers with a 4,096 hidden size and 64 attention heads. Its architecture combines CSA and HCA attention with manifold-constrained hyper-connections and supports a 1M-token context window. It features FP4 expert weights, FP8 quantization, and a speculative decoding module for faster generation.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (deepseek-ai/DeepSeek-V4-Flash-0731). Released under MIT. Further reading: Paper · Blog
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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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