Mistral Small 3.1 24B Instruct vs Qwen3-235B-A22B-Thinking-2507
Qwen3-235B-A22B-Thinking-2507 leads the LLM Stats Score 28.1 to 4.2.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3-235B-A22B-Thinking-2507 leads the overall LLM Stats Score 28.1 to 4.2, ranking #134 overall.
In the 2 individual benchmarks reported for both models, Qwen3-235B-A22B-Thinking-2507 wins 2; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Mistral Small 3.1 24B Instruct
- you are already invested in the Mistral AI ecosystem
Choose Qwen3-235B-A22B-Thinking-2507
- overall performance matters — it scores 28.1 and ranks #134 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Jul 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for Mistral Small 3.1 24B Instruct · 25 for Qwen3-235B-A22B-Thinking-2507
Mistral Small 3.1 24B Instruct outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 2 benchmarks (GPQA, MMLU-Pro).
Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3-235B-A22B-Thinking-2507 has 211.0B more parameters than Mistral Small 3.1 24B Instruct, making it 879.2% larger.
Context Window
Maximum input and output token capacity
Only Qwen3-235B-A22B-Thinking-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Thinking-2507 specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Small 3.1 24B Instruct supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.
Mistral Small 3.1 24B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Small 3.1 24B Instruct
Qwen3-235B-A22B-Thinking-2507
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Mistral Small 3.1 24B Instruct was released on 2025-03-17, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.
Qwen3-235B-A22B-Thinking-2507 is 4 months newer than Mistral Small 3.1 24B Instruct.
Mar 17, 2025
1.5 years ago
Jul 25, 2025
1.1 years ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Small 3.1 24B Instruct and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Small 3.1 24B Instruct vs Qwen3-235B-A22B-Thinking-2507.
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