DeepSeek V3.1
671.2B total, 37.7B active · 160k context · MIT License · released 2025-08-21
chatcodingagenticreasoning
In short
DeepSeek V3.1 is an open model from DeepSeek with 671.2B parameters (37.7B active per token). At mlx-4bit, DeepSeek V3.1 needs about 353 GB of memory at 8k context and 353 GB at 8k, counting the weights, the KV cache and runtime buffers. Nothing we price in Germany runs DeepSeek V3.1 fully in memory at 8k context at a usable speed; see the table for what comes closest.
Updated . Speeds are estimates; how they are worked out.
What to run it on in Germany
Fully in memory at 8k context, priced at retailers today.
Something we price holds it fully in memory, but none reaches 15 tok/s, our bar for recommending it. The table below has the speeds.
All hardware that runs it
Everything we price, best value first. Two cards split the model by layers.
| Hardware | Quant | Fits | Decode | Price | tok/s per 1,000 |
|---|---|---|---|---|---|
| Mac Studio M3 Ultra 512GB | Q4_K_M | fits | 14 tok/s | 18.995 € | 0.7 |
39 other cards and machines we price cannot hold it at this context.
Memory needed
Weights, KV cache and runtime buffers at each context length (KV cache at fp16).
| Quant | File | @8k | @32k | @64k | @128k |
|---|---|---|---|---|---|
| mlx-4bitmlx | 351.7 GB | 353.0 GB | 354.7 GB | 357.0 GB | 361.7 GB |
| Q4_K_Mgguf | 377.6 GB | 378.8 GB | 380.6 GB | 382.9 GB | 387.6 GB |
| Q5_K_Mgguf | 443.5 GB | 444.7 GB | 446.5 GB | 448.8 GB | 453.5 GB |
| Q6_Kgguf | 513.5 GB | 514.7 GB | 516.5 GB | 518.8 GB | 523.5 GB |
| mlx-8bitmlx | 664.1 GB | 665.4 GB | 667.1 GB | 669.5 GB | 674.1 GB |
| Q8_0gguf | 664.3 GB | 665.6 GB | 667.3 GB | 669.7 GB | 674.3 GB |
Run it
Copy a command for the runtime you use.
- mlx-4bit
- LM Studio
lms get mlx-community/DeepSeek-V3.1-4bit - MLX
mlx_lm.server --model mlx-community/DeepSeek-V3.1-4bit
- LM Studio
- Q4_K_M
- Ollama
ollama run hf.co/unsloth/DeepSeek-V3.1-GGUF:Q4_K_M - LM Studio
lms get unsloth/DeepSeek-V3.1-GGUF@q4_k_m - llama.cpp
llama-server -hf unsloth/DeepSeek-V3.1-GGUF:Q4_K_M
- Ollama
- Q5_K_M
- Ollama
ollama run hf.co/unsloth/DeepSeek-V3.1-GGUF:Q5_K_M - LM Studio
lms get unsloth/DeepSeek-V3.1-GGUF@q5_k_m - llama.cpp
llama-server -hf unsloth/DeepSeek-V3.1-GGUF:Q5_K_M
- Ollama
- Q6_K
- Ollama
ollama run hf.co/unsloth/DeepSeek-V3.1-GGUF:Q6_K - LM Studio
lms get unsloth/DeepSeek-V3.1-GGUF@q6_k - llama.cpp
llama-server -hf unsloth/DeepSeek-V3.1-GGUF:Q6_K
- Ollama
- mlx-8bit
- LM Studio
lms get mlx-community/DeepSeek-V3.1-8bit - MLX
mlx_lm.server --model mlx-community/DeepSeek-V3.1-8bit
- LM Studio
- Q8_0
- Ollama
ollama run hf.co/unsloth/DeepSeek-V3.1-GGUF:Q8_0 - LM Studio
lms get unsloth/DeepSeek-V3.1-GGUF@q8_0 - llama.cpp
llama-server -hf unsloth/DeepSeek-V3.1-GGUF:Q8_0
- Ollama
Notes
Hybrid thinking/non-thinking model switched via chat template; tool calling is supported in non-thinking mode. Requires FP8 weights/activations in UE8M0 scale format and mlp.gate.e_score_correction_bias in FP32. Excludes 13.4B parameters of multi-token-prediction layers, which local runtimes do not load.
Questions
- How much VRAM does DeepSeek V3.1 need?
- At mlx-4bit, DeepSeek V3.1 needs about 353 GB of memory at 8k context and 353 GB at 8k, counting the weights, the KV cache and runtime buffers.
- Can I run DeepSeek V3.1 on a 16 GB GPU?
- No: it does not fit in 16 GB at 8k context, even with system RAM.
- Can I run DeepSeek V3.1 on a 24 GB GPU?
- No: it does not fit in 24 GB at 8k context, even with system RAM.
- How do I run DeepSeek V3.1 locally?
- With Ollama: ollama run hf.co/unsloth/DeepSeek-V3.1-GGUF:Q4_K_M (the Q4_K_M build). LM Studio and llama.cpp commands are on this page.
- What licence is DeepSeek V3.1 released under?
- MIT License, which allows commercial use.