Devstral Small 1.1 is a 24B parameter open-weight language model for software engineering agents, developed by Mistral AI in collaboration with All Hands AI. Finetuned from Mistral Small 3.1 and released under the Apache 2.0 license, it fea…
Model details →Mistral: Devstral Small 1.1 vs Qwen: Qwen3 32B
Qwen: Qwen3 32B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Model details →Side-by-side comparison
| Capability | Mistral: Devstral Small 1.1 | Qwen: Qwen3 32B | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 131K | 131K | Tie |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.10 | $0.08 | 🏆 Qwen: Qwen3 32B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.30 | $0.28 | 🏆 Qwen: Qwen3 32B |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | Yes | 🏆 Qwen: Qwen3 32B |
Frequently asked questions
Is Mistral: Devstral Small 1.1 better than Qwen: Qwen3 32B?
Qwen: Qwen3 32B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Mistral: Devstral Small 1.1 and Qwen: Qwen3 32B?
Input: $0.10 vs $0.08 per 1M tokens. Output: $0.30 vs $0.28 per 1M tokens.
What context windows do Mistral: Devstral Small 1.1 and Qwen: Qwen3 32B support?
Mistral: Devstral Small 1.1 supports up to 131K tokens. Qwen: Qwen3 32B supports up to 131K tokens.
Do both Mistral: Devstral Small 1.1 and Qwen: Qwen3 32B support tool calling?
Mistral: Devstral Small 1.1: yes. Qwen: Qwen3 32B: yes.