DeepSeek R1 Distill Llama 8B vs Qwen3 8B
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
DeepSeek R1 Distill Llama 8B is more hardware-efficient — it needs 5.7 GB at Q4_K_M vs 5.8 GB for Qwen3 8B, fitting on 66 GPUs natively.
VRAM at each quantization (8k context)
| Quant | DeepSeek R1 Distill Llama 8B | Qwen3 8B | Diff |
|---|---|---|---|
| FP16 | 19.1 GB | 19.3 GB | -1% |
| Q8 | 10.2 GB | 10.3 GB | -1% |
| Q6_K | 7.9 GB | 8.1 GB | -2% |
| Q5_K_M | 6.8 GB | 7.0 GB | -2% |
| Q4_K_M | 5.7 GB | 5.8 GB | -3% |
| Q3_K_M | 4.8 GB | 4.9 GB | -3% |
| Q2_K | 3.9 GB | 4.0 GB | -4% |
Diff is DeepSeek R1 Distill Llama 8B relative to Qwen3 8B. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | DeepSeek R1 Distill Llama 8B | Qwen3 8B |
|---|---|---|
| Org | DeepSeek | Alibaba |
| Parameters | 8B | 8B |
| Architecture | Dense | Dense |
| Context | 125k tokens | 128k tokens |
| Modalities | text | text |
| License | MIT | Apache 2.0 |
| Commercial | Yes | Yes |
| Released | 2025-01-20 | 2025-04-29 |
| GPUs (native) | 66 / 67 | 66 / 67 |
Benchmark scores
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 Qwen3 8B.
GPUs that run only Qwen3 8B(0)
Every GPU that runs Qwen3 8B 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:
Choose Qwen3 8B if:
- • Long context matters — it supports 128k tokens vs 125k
Frequently asked questions
- Which is better, DeepSeek R1 Distill Llama 8B or Qwen3 8B?
- DeepSeek R1 Distill Llama 8B is more hardware-efficient, needing 5.7 GB at Q4_K_M vs 5.8 GB.
- How much VRAM does DeepSeek R1 Distill Llama 8B need vs Qwen3 8B?
- At Q4_K_M quantization with 8k context, DeepSeek R1 Distill Llama 8B needs approximately 5.7 GB of VRAM, while Qwen3 8B needs 5.8 GB. At FP16, DeepSeek R1 Distill Llama 8B requires 19.1 GB vs 19.3 GB for Qwen3 8B.
- Can you run DeepSeek R1 Distill Llama 8B on the same GPUs as Qwen3 8B?
- 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 Qwen3 8B, and no GPU can run Qwen3 8B without also fitting DeepSeek R1 Distill Llama 8B.
- What is the difference between DeepSeek R1 Distill Llama 8B and Qwen3 8B?
- DeepSeek R1 Distill Llama 8B has 8B parameters (dense) with a 125k context window. Qwen3 8B has 8B parameters (dense) with a 128k context window. Licensing differs: DeepSeek R1 Distill Llama 8B is MIT while Qwen3 8B is Apache 2.0.
- Which model fits in 24 GB of VRAM, DeepSeek R1 Distill Llama 8B or Qwen3 8B?
- Both fit in 24 GB of VRAM at Q4_K_M — DeepSeek R1 Distill Llama 8B needs 5.7 GB and Qwen3 8B needs 5.8 GB.