Overview
DeepSeek-V4-Pro is a large language model from deepseek-ai, the lab behind the DeepSeek V3 and R1 series.
- License: Mit
- Context length: 1M tokens
- Languages: Multilingual
- Minimum hardware: ~482 GB VRAM
- Strengths: reasoning, coding and on-device inference
Highlights
- Step-by-step reasoning — works through multi-stage math, logic, and planning before answering.
- Code generation & review — writes, debugs, and refactors, reading large repos in one pass.
- Multilingual — drafting, translation, and analysis across languages.
- 1M context, MoE — 861.6B total parameters with sparse per-token activation.
What it is good at
The capability flags on DeepSeek-V4-Pro are thinking, reasoning, code, and multilingual. Those map to a few concrete jobs.
- Step-by-step reasoning — the thinking and reasoning caps mean it works through multi-stage math, logic, and planning problems before committing to an answer.
- Code generation and review — the code capability covers writing functions, debugging, and refactoring, and the 1M-token context lets it read large repositories in a single pass.
- Multilingual text work — drafting, translating, and analyzing content across languages without switching to a separate model.
Running it locally
At 861.6B parameters in FP8, DeepSeek-V4-Pro is a data-center-scale model. The full unquantized weights run to roughly 862GB, which exceeds 8x H100 80GB (640GB) and instead needs a setup like 8x H200 141GB or a two-node H100 cluster; quantized builds cut the footprint but still expect a multi-GPU machine. The 1,048,576-token context adds KV-cache memory on top of the weights, so plan VRAM with the context length you actually use in mind.
huggingface-cli download deepseek-ai/DeepSeek-V4-Pro
From there you can serve it with vLLM, which supports MoE expert parallelism and KV-cache management for models this size, or load it through Transformers. In Atomic Chat the model is available as a one-click entry, so you skip the manual serving setup and run it on-device.
License
DeepSeek-V4-Pro is released under the MIT license. That permits commercial use, modification, fine-tuning, and redistribution with no royalty, as long as the license notice is preserved.