DeepSeek R1 Distill Llama 8B — VRAM, speed & local setup
Written by Jakub Rusinowski · Last updated
A highly efficient distilled version based on Llama 3. Incredible reasoning performance for its size.
DeepSeek R1 Distill Llama 8B needs about 6 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.
VRAM and speed by quantization
Quoted against NVIDIA RTX 4090 (24 GB). Includes the KV cache at 8K context, so it reads higher than the headline figure.
| Quant | Memory | VRAM | Speed (est.) | Fit |
|---|---|---|---|---|
| Q2_K 2.63 bpw | 4.5 GB | ~155 tok/s | Fits | |
| Q3_K_M 3.41 bpw | 5.3 GB | ~134 tok/s | Fits | |
| Q4_K_M 4.83 bpw | 6.7 GB | ~107 tok/s | Fits | |
| Q5_K_M 5.67 bpw | 7.5 GB | ~96 tok/s | Fits | |
| Q6_K 6.56 bpw | 8.4 GB | ~86 tok/s | Fits | |
| Q8_0 8.50 bpw | 10.4 GB | ~70 tok/s | Fits | |
| F16 16.00 bpw | 17.9 GB | ~41 tok/s | Fits |
Black marker = usable memory on the NVIDIA RTX 4090 (24 GB). Estimates from the memory-bandwidth roofline on the methodology page. DeepSeek R1 Distill Llama 8B VRAM calculator →
Get DeepSeek R1 Distill Llama 8B running
The cheapest catalogued GPU that runs DeepSeek R1 Distill Llama 8B is the Intel Arc B570 (10 GB).
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How to run DeepSeek R1 Distill Llama 8B
Install Ollama, then run:
ollama run deepseek-r1:8bSpecifications
Curated — A hand-written entry from before this catalogue recorded its sources. The figures are long-standing but their provenance is not on file.
- Parameters
- 8 Billion
- Context window
- 128,000
- Architecture
- Dense
- Provider
- DeepSeek
- Licence
- MIT
- Practical deployment
- Laptop
- Specified at
- Q4_K_M
- System RAM
- 16 GB
- Record updated
- 2025-01-20
Commercial use permitted. No usage restrictions beyond attribution.
Quality and use cases
Scores as published by the model’s authors or an independent evaluator — quality, not throughput, and not measured by us.
Can I run DeepSeek R1 Distill Llama 8B on my GPU?
- DeepSeek R1 Distill Llama 8B on AMD Radeon RX 7800 XT
- DeepSeek R1 Distill Llama 8B on AMD Radeon RX 7900 XT
- DeepSeek R1 Distill Llama 8B on AMD Radeon RX 7900 XTX
- DeepSeek R1 Distill Llama 8B on AMD Radeon RX 9060 XT 16GB
- DeepSeek R1 Distill Llama 8B on AMD Radeon RX 9070
- DeepSeek R1 Distill Llama 8B on AMD Radeon RX 9070 XT
- DeepSeek R1 Distill Llama 8B on Apple M1
- DeepSeek R1 Distill Llama 8B on Apple M1 Pro
- DeepSeek R1 Distill Llama 8B on Apple M2 Pro
- DeepSeek R1 Distill Llama 8B on Apple M3 Pro
- DeepSeek R1 Distill Llama 8B on Apple M4
- DeepSeek R1 Distill Llama 8B on Apple M5
- DeepSeek R1 Distill Llama 8B on Intel Arc B580
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 3060 (12GB)
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 3090
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4060 Ti 16GB
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4070
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4070 Super
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4070 Ti
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4070 Ti Super
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4080
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4080 Super
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 4090
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 5060 Ti 16GB
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 5070
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 5070 Ti
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 5080
- DeepSeek R1 Distill Llama 8B on NVIDIA GeForce RTX 5090
- DeepSeek R1 Distill Llama 8B on NVIDIA L40S
- DeepSeek R1 Distill Llama 8B on NVIDIA RTX 6000 Ada Generation
Other DeepSeek R1 sizes
DeepSeek R1 Distill Llama 8B — frequently asked questions
How much VRAM does DeepSeek R1 Distill Llama 8B need?
About 6 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does DeepSeek R1 Distill Llama 8B run on an RTX 4090 (24 GB)?
Yes. DeepSeek R1 Distill Llama 8B needs about 6 GB at Q4_K_M, inside a 24 GB card, at an estimated 107 tokens/sec.
How do I run DeepSeek R1 Distill Llama 8B locally?
Install Ollama and run `ollama run deepseek-r1:8b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does DeepSeek R1 come in?
DeepSeek R1 Distill Llama 8B (6 GB), DeepSeek R1 Distill Qwen 32B (20 GB), DeepSeek R1 Distill Qwen 14B (9 GB), DeepSeek R1 (671B) (406 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.