Mixtral 8x22B Instruct v0.1 vs Qwen 2.5 72B Instruct
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Qwen 2.5 72B Instruct is more hardware-efficient — it needs 43.3 GB at Q4_K_M vs 81.1 GB for Mixtral 8x22B Instruct v0.1, fitting on 38 GPUs natively. Mixtral 8x22B Instruct v0.1 is a Mixture of Experts model — it has 141B total parameters but only 39B are active per token, making inference faster than its total size suggests.
VRAM at each quantization (8k context)
| Quant | Mixtral 8x22B Instruct v0.1 | Qwen 2.5 72B Instruct | Diff |
|---|---|---|---|
| FP16 | 317.9 GB | 164.3 GB | +94% |
| Q8 | 160.0 GB | 83.6 GB | +91% |
| Q6_K | 120.5 GB | 63.5 GB | +90% |
| Q5_K_M | 100.8 GB | 53.4 GB | +89% |
| Q4_K_M | 81.1 GB | 43.3 GB | +87% |
| Q3_K_M | 65.3 GB | 35.3 GB | +85% |
| Q2_K | 49.5 GB | 27.2 GB | +82% |
Diff is Mixtral 8x22B Instruct v0.1 relative to Qwen 2.5 72B Instruct. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Mixtral 8x22B Instruct v0.1 | Qwen 2.5 72B Instruct |
|---|---|---|
| Org | Mistral AI | Alibaba |
| Parameters | 141B | 72B |
| Architecture | MoE (39B active) | Dense |
| Context | 64k tokens | 125k tokens |
| Modalities | text | text |
| License | Apache 2.0 | Qwen |
| Commercial | Yes | Yes |
| Released | 2024-04-17 | 2024-09-19 |
| GPUs (native) | 22 / 67 | 38 / 67 |
Benchmark scores
| Benchmark | Mixtral 8x22B Instruct v0.1 | Qwen 2.5 72B Instruct |
|---|---|---|
| MMLU-Pro | 40.0 | 58.1 |
| IFEval | 71.8 | 86.4 |
| MATH | 41.8 | 83.1 |
| HumanEval | 76.2 | 86.6 |
| Arena ELO | 1147.0 | 1259.0 |
Green = higher score (better). — = not yet available.
GPUs that run only Mixtral 8x22B Instruct v0.1(0)
Every GPU that runs Mixtral 8x22B Instruct v0.1 also runs Qwen 2.5 72B Instruct.
GPUs that run only Qwen 2.5 72B Instruct(16)
- NVIDIA RTX 509032 GB
- NVIDIA A100 40GB40 GB
- NVIDIA L40S48 GB
- NVIDIA RTX A600048 GB
- NVIDIA RTX 6000 Ada48 GB
- Apple M5 (32GB)32 GB
- Apple M4 Max (48GB)48 GB
- Apple M4 Pro (48GB)48 GB
- Apple M4 (32GB)32 GB
- Apple M3 Max (48GB)48 GB
- +6 more
GPUs that run both natively(22)
- NVIDIA H100 80GB80 GB
- NVIDIA A100 80GB80 GB
- NVIDIA DGX Spark (128GB)128 GB
- AMD Instinct MI300X192 GB
- AMD Strix Halo (128GB)128 GB
- AMD Strix Halo (96GB)96 GB
- AMD Strix Halo (64GB)64 GB
- Apple M4 Ultra (384GB)384 GB
- Apple M4 Ultra (192GB)192 GB
- Apple M4 Max (128GB)128 GB
- Apple M4 Max (96GB)96 GB
- Apple M4 Max (64GB)64 GB
- +10 more GPUs run both
Which should you use?
Choose Mixtral 8x22B Instruct v0.1 if:
- • You want maximum capability and have a 82 GB+ GPU
- • You want fast inference — MoE only activates 39B params per token
Choose Qwen 2.5 72B Instruct if:
- • You have limited VRAM — it's a smaller model needing 43.3 GB vs 81.1 GB
- • Long context matters — it supports 125k tokens vs 64k
- • Benchmark quality matters — scores 58.1 vs 40.0 on MMLU-Pro
Frequently asked questions
- Which is better, Mixtral 8x22B Instruct v0.1 or Qwen 2.5 72B Instruct?
- Mixtral 8x22B Instruct v0.1 has 141B parameters vs 72B for Qwen 2.5 72B Instruct, so Mixtral 8x22B Instruct v0.1 is the larger model. Qwen 2.5 72B Instruct is more hardware-efficient, needing 43.3 GB at Q4_K_M vs 81.1 GB. Qwen 2.5 72B Instruct runs on more GPUs natively (38 vs 22). On MMLU-Pro, Qwen 2.5 72B Instruct scores higher (58.1 vs 40.0).
- How much VRAM does Mixtral 8x22B Instruct v0.1 need vs Qwen 2.5 72B Instruct?
- At Q4_K_M quantization with 8k context, Mixtral 8x22B Instruct v0.1 needs approximately 81.1 GB of VRAM, while Qwen 2.5 72B Instruct needs 43.3 GB. At FP16, Mixtral 8x22B Instruct v0.1 requires 317.9 GB vs 164.3 GB for Qwen 2.5 72B Instruct.
- Can you run Mixtral 8x22B Instruct v0.1 on the same GPUs as Qwen 2.5 72B Instruct?
- Yes, 22 GPUs can run both natively in VRAM, including NVIDIA H100 80GB, NVIDIA A100 80GB, NVIDIA DGX Spark (128GB). However, no GPU can run Mixtral 8x22B Instruct v0.1 without also fitting Qwen 2.5 72B Instruct, and 16 GPUs can run Qwen 2.5 72B Instruct but not Mixtral 8x22B Instruct v0.1.
- What is the difference between Mixtral 8x22B Instruct v0.1 and Qwen 2.5 72B Instruct?
- Mixtral 8x22B Instruct v0.1 has 141B parameters (39B active, MoE) with a 64k context window. Qwen 2.5 72B Instruct has 72B parameters (dense) with a 125k context window. Licensing differs: Mixtral 8x22B Instruct v0.1 is Apache 2.0 while Qwen 2.5 72B Instruct is Qwen.
- Which model fits in 24 GB of VRAM, Mixtral 8x22B Instruct v0.1 or Qwen 2.5 72B Instruct?
- Neither fits in 24 GB at Q4_K_M — Mixtral 8x22B Instruct v0.1 needs 81.1 GB and Qwen 2.5 72B Instruct needs 43.3 GB. Both require at least a 48 GB GPU.