DeepSeek R1 Distill Llama 8B vs Llama 3.1 8B Instruct
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Both models need similar VRAM at Q4_K_M (5.7 GB). The choice comes down to benchmarks and architecture.
VRAM at each quantization (8k context)
| Quant | DeepSeek R1 Distill Llama 8B | Llama 3.1 8B Instruct | Diff |
|---|---|---|---|
| FP16 | 19.1 GB | 19.1 GB | +0% |
| Q8 | 10.2 GB | 10.2 GB | +0% |
| Q6_K | 7.9 GB | 7.9 GB | +0% |
| Q5_K_M | 6.8 GB | 6.8 GB | +0% |
| Q4_K_M | 5.7 GB | 5.7 GB | +0% |
| Q3_K_M | 4.8 GB | 4.8 GB | +0% |
| Q2_K | 3.9 GB | 3.9 GB | +0% |
Diff is DeepSeek R1 Distill Llama 8B relative to Llama 3.1 8B Instruct. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | DeepSeek R1 Distill Llama 8B | Llama 3.1 8B Instruct |
|---|---|---|
| Org | DeepSeek | Meta |
| Parameters | 8B | 8B |
| Architecture | Dense | Dense |
| Context | 125k tokens | 125k tokens |
| Modalities | text | text |
| License | MIT | Llama 3.1 Community |
| Commercial | Yes | Yes |
| Released | 2025-01-20 | 2024-07-23 |
| GPUs (native) | 66 / 67 | 66 / 67 |
Benchmark scores
| Benchmark | DeepSeek R1 Distill Llama 8B | Llama 3.1 8B Instruct |
|---|---|---|
| MMLU-Pro | 41.0 | 37.5 |
| GPQA | 49.0 | 30.4 |
| MATH | 89.1 | 48.0 |
| HumanEval | 81.3 | 72.6 |
Green = higher score (better). — = not yet available.
GPUs that run only DeepSeek R1 Distill Llama 8B(0)
Every GPU that runs DeepSeek R1 Distill Llama 8B also runs Llama 3.1 8B Instruct.
GPUs that run only Llama 3.1 8B Instruct(0)
Every GPU that runs Llama 3.1 8B Instruct also runs DeepSeek R1 Distill Llama 8B.
GPUs that run both natively(66)
- NVIDIA RTX 509032 GB
- NVIDIA RTX 409024 GB
- NVIDIA RTX 408016 GB
- NVIDIA RTX 4070 Ti12 GB
- NVIDIA RTX 407012 GB
- NVIDIA RTX 4060 Ti 16GB16 GB
- NVIDIA RTX 40608 GB
- NVIDIA RTX 309024 GB
- NVIDIA RTX 3090 Ti24 GB
- NVIDIA RTX 3080 10GB10 GB
- NVIDIA RTX 3060 12GB12 GB
- NVIDIA H100 80GB80 GB
- +54 more GPUs run both
Which should you use?
Choose DeepSeek R1 Distill Llama 8B if:
- • Benchmark quality matters — scores 41.0 vs 37.5 on MMLU-Pro
- • You need chain-of-thought reasoning
Choose Llama 3.1 8B Instruct if:
Frequently asked questions
- Which is better, DeepSeek R1 Distill Llama 8B or Llama 3.1 8B Instruct?
- On MMLU-Pro, DeepSeek R1 Distill Llama 8B scores higher (41.0 vs 37.5).
- How much VRAM does DeepSeek R1 Distill Llama 8B need vs Llama 3.1 8B Instruct?
- At Q4_K_M quantization with 8k context, DeepSeek R1 Distill Llama 8B needs approximately 5.7 GB of VRAM, while Llama 3.1 8B Instruct needs 5.7 GB. At FP16, DeepSeek R1 Distill Llama 8B requires 19.1 GB vs 19.1 GB for Llama 3.1 8B Instruct.
- Can you run DeepSeek R1 Distill Llama 8B on the same GPUs as Llama 3.1 8B Instruct?
- Yes, 66 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 4080. However, no GPU can run DeepSeek R1 Distill Llama 8B without also fitting Llama 3.1 8B Instruct, and no GPU can run Llama 3.1 8B Instruct without also fitting DeepSeek R1 Distill Llama 8B.
- What is the difference between DeepSeek R1 Distill Llama 8B and Llama 3.1 8B Instruct?
- DeepSeek R1 Distill Llama 8B has 8B parameters (dense) with a 125k context window. Llama 3.1 8B Instruct has 8B parameters (dense) with a 125k context window. Licensing differs: DeepSeek R1 Distill Llama 8B is MIT while Llama 3.1 8B Instruct is Llama 3.1 Community.
- Which model fits in 24 GB of VRAM, DeepSeek R1 Distill Llama 8B or Llama 3.1 8B Instruct?
- Both fit in 24 GB of VRAM at Q4_K_M — DeepSeek R1 Distill Llama 8B needs 5.7 GB and Llama 3.1 8B Instruct needs 5.7 GB.