Qwen 2.5 7B Instruct vs Mistral 7B Instruct v0.3
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Qwen 2.5 7B Instruct is more hardware-efficient — it needs 4.8 GB at Q4_K_M vs 5.3 GB for Mistral 7B Instruct v0.3, fitting on 66 GPUs natively.
VRAM at each quantization (8k context)
| Quant | Qwen 2.5 7B Instruct | Mistral 7B Instruct v0.3 | Diff |
|---|---|---|---|
| FP16 | 17.6 GB | 17.4 GB | +1% |
| Q8 | 9.0 GB | 9.3 GB | -3% |
| Q6_K | 6.9 GB | 7.3 GB | -5% |
| Q5_K_M | 5.8 GB | 6.3 GB | -7% |
| Q4_K_M | 4.8 GB | 5.3 GB | -9% |
| Q3_K_M | 3.9 GB | 4.5 GB | -12% |
| Q2_K | 3.1 GB | 3.6 GB | -15% |
Diff is Qwen 2.5 7B Instruct relative to Mistral 7B Instruct v0.3. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Qwen 2.5 7B Instruct | Mistral 7B Instruct v0.3 |
|---|---|---|
| Org | Alibaba | Mistral AI |
| Parameters | 7.6B | 7.25B |
| Architecture | Dense | Dense |
| Context | 125k tokens | 32k tokens |
| Modalities | text | text |
| License | Apache 2.0 | Apache 2.0 |
| Commercial | Yes | Yes |
| Released | 2024-09-19 | 2024-05-22 |
| GPUs (native) | 66 / 67 | 66 / 67 |
Benchmark scores
| Benchmark | Qwen 2.5 7B Instruct | Mistral 7B Instruct v0.3 |
|---|---|---|
| MMLU-Pro | 36.5 | 30.0 |
| GPQA | 36.4 | — |
| IFEval | 75.5 | 54.0 |
| MATH | 75.5 | — |
| HumanEval | 84.8 | 51.2 |
| Arena ELO | 1200.0 | — |
Green = higher score (better). — = not yet available.
GPUs that run only Qwen 2.5 7B Instruct(0)
Every GPU that runs Qwen 2.5 7B Instruct also runs Mistral 7B Instruct v0.3.
GPUs that run only Mistral 7B Instruct v0.3(0)
Every GPU that runs Mistral 7B Instruct v0.3 also runs Qwen 2.5 7B Instruct.
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 Qwen 2.5 7B Instruct if:
- • You want maximum capability and have a 5 GB+ GPU
- • Long context matters — it supports 125k tokens vs 32k
- • Benchmark quality matters — scores 36.5 vs 30.0 on MMLU-Pro
Choose Mistral 7B Instruct v0.3 if:
- • You have limited VRAM — it's a smaller model needing 5.3 GB vs 4.8 GB
Frequently asked questions
- Which is better, Qwen 2.5 7B Instruct or Mistral 7B Instruct v0.3?
- Qwen 2.5 7B Instruct has 7.6B parameters vs 7.25B for Mistral 7B Instruct v0.3, so Qwen 2.5 7B Instruct is the larger model. Qwen 2.5 7B Instruct is more hardware-efficient, needing 4.8 GB at Q4_K_M vs 5.3 GB. On MMLU-Pro, Qwen 2.5 7B Instruct scores higher (36.5 vs 30.0).
- How much VRAM does Qwen 2.5 7B Instruct need vs Mistral 7B Instruct v0.3?
- At Q4_K_M quantization with 8k context, Qwen 2.5 7B Instruct needs approximately 4.8 GB of VRAM, while Mistral 7B Instruct v0.3 needs 5.3 GB. At FP16, Qwen 2.5 7B Instruct requires 17.6 GB vs 17.4 GB for Mistral 7B Instruct v0.3.
- Can you run Qwen 2.5 7B Instruct on the same GPUs as Mistral 7B Instruct v0.3?
- Yes, 66 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 4080. However, no GPU can run Qwen 2.5 7B Instruct without also fitting Mistral 7B Instruct v0.3, and no GPU can run Mistral 7B Instruct v0.3 without also fitting Qwen 2.5 7B Instruct.
- What is the difference between Qwen 2.5 7B Instruct and Mistral 7B Instruct v0.3?
- Qwen 2.5 7B Instruct has 7.6B parameters (dense) with a 125k context window. Mistral 7B Instruct v0.3 has 7.25B parameters (dense) with a 32k context window.
- Which model fits in 24 GB of VRAM, Qwen 2.5 7B Instruct or Mistral 7B Instruct v0.3?
- Both fit in 24 GB of VRAM at Q4_K_M — Qwen 2.5 7B Instruct needs 4.8 GB and Mistral 7B Instruct v0.3 needs 5.3 GB.