Qwen3 8B vs Llama 3.1 8B Instruct
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Llama 3.1 8B Instruct 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 | Qwen3 8B | Llama 3.1 8B Instruct | Diff |
|---|---|---|---|
| FP16 | 19.3 GB | 19.1 GB | +1% |
| Q8 | 10.3 GB | 10.2 GB | +1% |
| Q6_K | 8.1 GB | 7.9 GB | +2% |
| Q5_K_M | 7.0 GB | 6.8 GB | +2% |
| Q4_K_M | 5.8 GB | 5.7 GB | +3% |
| Q3_K_M | 4.9 GB | 4.8 GB | +3% |
| Q2_K | 4.0 GB | 3.9 GB | +4% |
Diff is Qwen3 8B relative to Llama 3.1 8B Instruct. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Qwen3 8B | Llama 3.1 8B Instruct |
|---|---|---|
| Org | Alibaba | Meta |
| Parameters | 8B | 8B |
| Architecture | Dense | Dense |
| Context | 128k tokens | 125k tokens |
| Modalities | text | text |
| License | Apache 2.0 | Llama 3.1 Community |
| Commercial | Yes | Yes |
| Released | 2025-04-29 | 2024-07-23 |
| GPUs (native) | 66 / 67 | 66 / 67 |
GPUs that run only Qwen3 8B(0)
Every GPU that runs Qwen3 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 Qwen3 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 Qwen3 8B if:
- • Long context matters — it supports 128k tokens vs 125k
- • You need chain-of-thought reasoning
Choose Llama 3.1 8B Instruct if:
Frequently asked questions
- Which is better, Qwen3 8B or Llama 3.1 8B Instruct?
- Llama 3.1 8B Instruct is more hardware-efficient, needing 5.7 GB at Q4_K_M vs 5.8 GB.
- How much VRAM does Qwen3 8B need vs Llama 3.1 8B Instruct?
- At Q4_K_M quantization with 8k context, Qwen3 8B needs approximately 5.8 GB of VRAM, while Llama 3.1 8B Instruct needs 5.7 GB. At FP16, Qwen3 8B requires 19.3 GB vs 19.1 GB for Llama 3.1 8B Instruct.
- Can you run Qwen3 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 Qwen3 8B without also fitting Llama 3.1 8B Instruct, and no GPU can run Llama 3.1 8B Instruct without also fitting Qwen3 8B.
- What is the difference between Qwen3 8B and Llama 3.1 8B Instruct?
- Qwen3 8B has 8B parameters (dense) with a 128k context window. Llama 3.1 8B Instruct has 8B parameters (dense) with a 125k context window. Licensing differs: Qwen3 8B is Apache 2.0 while Llama 3.1 8B Instruct is Llama 3.1 Community.
- Which model fits in 24 GB of VRAM, Qwen3 8B or Llama 3.1 8B Instruct?
- Both fit in 24 GB of VRAM at Q4_K_M — Qwen3 8B needs 5.8 GB and Llama 3.1 8B Instruct needs 5.7 GB.