Model ID
deepseek-ai/DeepSeek-V4-Pro
Capabilities
DeepSeek V4 Pro
DeepSeek V4 Pro is an ultra-large Mixture-of-Experts model designed for high-performance long-context reasoning and large-scale deployment. It features 1.6T total parameters with approximately 49B activated, using 384 routed experts with 6 selected per token across a 61-layer architecture with 7,168 hidden size and 128 attention heads. Built with hybrid compressed attention mechanisms and manifold-constrained hyper-connections, it supports up to a 1M token context window. With FP4 and FP8 mixed precision and advanced optimization techniques, it delivers strong efficiency, stability, and agentic reasoning performance across complex workloads.
About this model
DeepSeek V4 Pro is an ultra-large Mixture-of-Experts model designed for high-performance long-context reasoning and large-scale deployment. It features 1.6T total parameters with approximately 49B activated, using 384 routed experts with 6 selected per token across a 61-layer architecture with 7,168 hidden size and 128 attention heads. Built with hybrid compressed attention mechanisms and manifold-constrained hyper-connections, it supports up to a 1M token context window. With FP4 and FP8 mixed precision and advanced optimization techniques, it delivers strong efficiency, stability, and agentic reasoning performance across complex workloads.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (deepseek-ai/DeepSeek-V4-Pro). Released under MIT. Further reading: 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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