Mixtral 8x7B Instruct v0.1 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 27.4 GB for Mixtral 8x7B Instruct v0.1, fitting on 66 GPUs natively. Mixtral 8x7B Instruct v0.1 is a Mixture of Experts model — it has 46.7B total parameters but only 12.9B are active per token, making inference faster than its total size suggests.
VRAM at each quantization (8k context)
| Quant | Mixtral 8x7B Instruct v0.1 | Llama 3.1 8B Instruct | Diff |
|---|---|---|---|
| FP16 | 105.8 GB | 19.1 GB | +453% |
| Q8 | 53.5 GB | 10.2 GB | +427% |
| Q6_K | 40.4 GB | 7.9 GB | +410% |
| Q5_K_M | 33.9 GB | 6.8 GB | +398% |
| Q4_K_M | 27.4 GB | 5.7 GB | +381% |
| Q3_K_M | 22.1 GB | 4.8 GB | +362% |
| Q2_K | 16.9 GB | 3.9 GB | +334% |
Diff is Mixtral 8x7B Instruct v0.1 relative to Llama 3.1 8B Instruct. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Mixtral 8x7B Instruct v0.1 | Llama 3.1 8B Instruct |
|---|---|---|
| Org | Mistral AI | Meta |
| Parameters | 46.7B | 8B |
| Architecture | MoE (12.9B active) | Dense |
| Context | 32k tokens | 125k tokens |
| Modalities | text | text |
| License | Apache 2.0 | Llama 3.1 Community |
| Commercial | Yes | Yes |
| Released | 2023-12-11 | 2024-07-23 |
| GPUs (native) | 46 / 67 | 66 / 67 |
Benchmark scores
| Benchmark | Mixtral 8x7B Instruct v0.1 | Llama 3.1 8B Instruct |
|---|---|---|
| MMLU-Pro | 29.7 | 37.5 |
| IFEval | 54.8 | 77.4 |
| HumanEval | 45.1 | 72.6 |
| Arena ELO | 1114.0 | 1176.0 |
Green = higher score (better). — = not yet available.
GPUs that run only Mixtral 8x7B Instruct v0.1(0)
Every GPU that runs Mixtral 8x7B Instruct v0.1 also runs Llama 3.1 8B Instruct.
GPUs that run only Llama 3.1 8B Instruct(20)
- 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 3080 10GB10 GB
- NVIDIA RTX 3060 12GB12 GB
- AMD Radeon RX 6800 XT16 GB
- Apple M5 (16GB)16 GB
- Apple M4 (16GB)16 GB
- +10 more
GPUs that run both natively(46)
- NVIDIA RTX 509032 GB
- NVIDIA RTX 409024 GB
- NVIDIA RTX 309024 GB
- NVIDIA RTX 3090 Ti24 GB
- NVIDIA H100 80GB80 GB
- NVIDIA A100 80GB80 GB
- NVIDIA A100 40GB40 GB
- NVIDIA L40S48 GB
- NVIDIA RTX A600048 GB
- NVIDIA RTX 6000 Ada48 GB
- NVIDIA DGX Spark (128GB)128 GB
- AMD Radeon RX 7900 XTX24 GB
- +34 more GPUs run both
Which should you use?
Choose Mixtral 8x7B Instruct v0.1 if:
- • You want maximum capability and have a 28 GB+ GPU
- • You want fast inference — MoE only activates 12.9B params per token
Choose Llama 3.1 8B Instruct if:
- • You have limited VRAM — it's a smaller model needing 5.7 GB vs 27.4 GB
- • Long context matters — it supports 125k tokens vs 32k
- • Benchmark quality matters — scores 37.5 vs 29.7 on MMLU-Pro
Frequently asked questions
- Which is better, Mixtral 8x7B Instruct v0.1 or Llama 3.1 8B Instruct?
- Mixtral 8x7B Instruct v0.1 has 46.7B parameters vs 8B for Llama 3.1 8B Instruct, so Mixtral 8x7B Instruct v0.1 is the larger model. Llama 3.1 8B Instruct is more hardware-efficient, needing 5.7 GB at Q4_K_M vs 27.4 GB. Llama 3.1 8B Instruct runs on more GPUs natively (66 vs 46). On MMLU-Pro, Llama 3.1 8B Instruct scores higher (37.5 vs 29.7).
- How much VRAM does Mixtral 8x7B Instruct v0.1 need vs Llama 3.1 8B Instruct?
- At Q4_K_M quantization with 8k context, Mixtral 8x7B Instruct v0.1 needs approximately 27.4 GB of VRAM, while Llama 3.1 8B Instruct needs 5.7 GB. At FP16, Mixtral 8x7B Instruct v0.1 requires 105.8 GB vs 19.1 GB for Llama 3.1 8B Instruct.
- Can you run Mixtral 8x7B Instruct v0.1 on the same GPUs as Llama 3.1 8B Instruct?
- Yes, 46 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 3090. However, no GPU can run Mixtral 8x7B Instruct v0.1 without also fitting Llama 3.1 8B Instruct, and 20 GPUs can run Llama 3.1 8B Instruct but not Mixtral 8x7B Instruct v0.1.
- What is the difference between Mixtral 8x7B Instruct v0.1 and Llama 3.1 8B Instruct?
- Mixtral 8x7B Instruct v0.1 has 46.7B parameters (12.9B active, MoE) with a 32k context window. Llama 3.1 8B Instruct has 8B parameters (dense) with a 125k context window. Licensing differs: Mixtral 8x7B Instruct v0.1 is Apache 2.0 while Llama 3.1 8B Instruct is Llama 3.1 Community.
- Which model fits in 24 GB of VRAM, Mixtral 8x7B Instruct v0.1 or Llama 3.1 8B Instruct?
- Only Llama 3.1 8B Instruct fits in 24 GB at Q4_K_M (5.7 GB). Mixtral 8x7B Instruct v0.1 needs 27.4 GB, requiring a larger GPU.