Mistral Small 24B vs Qwen2.5 32B
Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.
| Mistral Small 24B | Qwen2.5 32B | |
|---|---|---|
| Parameters | 24B | 32B |
| Context window | 32K tokens | 128K tokens |
| License | Apache-2.0 | Apache-2.0 |
| ~VRAM @ 4-bit (Q4_K_M) | ~14 GB | ~20 GB |
| ~VRAM @ 8-bit (Q8_0) | ~25 GB | ~34 GB |
| Minimum device | Intel Arc A770 16GB | NVIDIA GeForce RTX 3090 |
| Recommended device | Supermicro 8x H100 SuperServer | Supermicro 8x H100 SuperServer |
| Deployment | Local / on-prem | Hybrid |
| Capabilities | Tools, Code, Multilingual, Long context | Tools, Code, Reasoning, Multilingual, Long context |
Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.
Bottom line
Mistral Small 24B (~24B) is lighter than Qwen2.5 32B (~32B), so it runs on more modest hardware, while Qwen2.5 32B trades a larger footprint for more capacity. At 4-bit, Mistral Small 24B needs about 14GB versus ~20GB, a meaningful gap when choosing a GPU. Qwen2.5 32B advertises the longer context window (128K vs 32K), which helps with long documents. Both ship under permissive licenses, easing commercial use. Minimum viable hardware differs: Mistral Small 24B starts on a Intel Arc A770 16GB, Qwen2.5 32B on a NVIDIA GeForce RTX 3090. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.
Pick Mistral Small 24B if you want the lighter footprint and cheaper hardware.
Pick Qwen2.5 32B if you have the memory to spare and want the larger model, or you need the longer 128K context window.
A 24GB card at 4-bit. A capable, openly-licensed mid-size model between 14B and 32B.
A 24GB card (RTX 3090/4090) or 32GB+ Mac runs it well at 4-bit. The sweet spot for capable single-box agents.
Run the winner on hardware you control
Pick the model that fits your footprint, then turn the right machine into a private AI Business OS — no per-seat data leaving your premises.