Mistral Small 3.1 24B Instruct vs Qwen 3.6 27B
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Mistral Small 3.1 24B Instruct is more hardware-efficient — it needs 14.9 GB at Q4_K_M vs 16.9 GB for Qwen 3.6 27B, fitting on 61 GPUs natively.
VRAM at each quantization (8k context)
| Quant | Mistral Small 3.1 24B Instruct | Qwen 3.6 27B | Diff |
|---|---|---|---|
| FP16 | 55.3 GB | 62.3 GB | -11% |
| Q8 | 28.4 GB | 32.0 GB | -11% |
| Q6_K | 21.7 GB | 24.5 GB | -12% |
| Q5_K_M | 18.3 GB | 20.7 GB | -12% |
| Q4_K_M | 14.9 GB | 16.9 GB | -12% |
| Q3_K_M | 12.3 GB | 13.9 GB | -12% |
| Q2_K | 9.6 GB | 10.9 GB | -12% |
Diff is Mistral Small 3.1 24B Instruct relative to Qwen 3.6 27B. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Mistral Small 3.1 24B Instruct | Qwen 3.6 27B |
|---|---|---|
| Org | Mistral AI | Alibaba |
| Parameters | 24B | 27B |
| Architecture | Dense | Dense |
| Context | 128k tokens | 256k tokens |
| Modalities | text, vision | text, vision |
| License | Apache 2.0 | Apache 2.0 |
| Commercial | Yes | Yes |
| Released | 2025-03-17 | 2026-04-01 |
| GPUs (native) | 61 / 67 | 61 / 67 |
GPUs that run only Mistral Small 3.1 24B Instruct(0)
Every GPU that runs Mistral Small 3.1 24B Instruct also runs Qwen 3.6 27B.
GPUs that run only Qwen 3.6 27B(0)
Every GPU that runs Qwen 3.6 27B also runs Mistral Small 3.1 24B Instruct.
GPUs that run both natively(61)
- 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 309024 GB
- NVIDIA RTX 3090 Ti24 GB
- NVIDIA RTX 3060 12GB12 GB
- NVIDIA H100 80GB80 GB
- NVIDIA A100 80GB80 GB
- NVIDIA A100 40GB40 GB
- +49 more GPUs run both
Which should you use?
Choose Mistral Small 3.1 24B Instruct if:
- • You have limited VRAM — it's a smaller model needing 14.9 GB vs 16.9 GB
Choose Qwen 3.6 27B if:
- • You want maximum capability and have a 17 GB+ GPU
- • Long context matters — it supports 256k tokens vs 128k
- • You need chain-of-thought reasoning
Frequently asked questions
- Which is better, Mistral Small 3.1 24B Instruct or Qwen 3.6 27B?
- Mistral Small 3.1 24B Instruct has 24B parameters vs 27B for Qwen 3.6 27B, so Qwen 3.6 27B is the larger model. Mistral Small 3.1 24B Instruct is more hardware-efficient, needing 14.9 GB at Q4_K_M vs 16.9 GB.
- How much VRAM does Mistral Small 3.1 24B Instruct need vs Qwen 3.6 27B?
- At Q4_K_M quantization with 8k context, Mistral Small 3.1 24B Instruct needs approximately 14.9 GB of VRAM, while Qwen 3.6 27B needs 16.9 GB. At FP16, Mistral Small 3.1 24B Instruct requires 55.3 GB vs 62.3 GB for Qwen 3.6 27B.
- Can you run Mistral Small 3.1 24B Instruct on the same GPUs as Qwen 3.6 27B?
- Yes, 61 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 4080. However, no GPU can run Mistral Small 3.1 24B Instruct without also fitting Qwen 3.6 27B, and no GPU can run Qwen 3.6 27B without also fitting Mistral Small 3.1 24B Instruct.
- What is the difference between Mistral Small 3.1 24B Instruct and Qwen 3.6 27B?
- Mistral Small 3.1 24B Instruct has 24B parameters (dense) with a 128k context window. Qwen 3.6 27B has 27B parameters (dense) with a 256k context window.
- Which model fits in 24 GB of VRAM, Mistral Small 3.1 24B Instruct or Qwen 3.6 27B?
- Both fit in 24 GB of VRAM at Q4_K_M — Mistral Small 3.1 24B Instruct needs 14.9 GB and Qwen 3.6 27B needs 16.9 GB.