Mistral Small 3.1 24B Base vs Qwen3 235B A22B
Qwen3 235B A22B leads the LLM Stats Score 15.6 to 0.3. Qwen3 235B A22B is 1.5x cheaper per token.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 235B A22B leads the overall LLM Stats Score 15.6 to 0.3, ranking #232 overall.
In the 3 individual benchmarks reported for both models, Qwen3 235B A22B wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 235B A22B is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Mistral Small 3.1 24B Base
- you want predictable pricing at $0.10/M input and $0.30/M output
Choose Qwen3 235B A22B
- overall performance matters — it scores 15.6 and ranks #232 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- cost matters — it's about 1.5x cheaper per token
- you want the most recent training data — it shipped Apr 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for Mistral Small 3.1 24B Base · 23 for Qwen3 235B A22B
Mistral Small 3.1 24B Base outperforms in 0 benchmarks, while Qwen3 235B A22B is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro).
Qwen3 235B A22B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Mistral Small 3.1 24B Base ($0.10/1M tokens) costs the same as Qwen3 235B A22B ($0.10/1M tokens).
For output processing, Mistral Small 3.1 24B Base ($0.30/1M tokens) is 3.0x more expensive than Qwen3 235B A22B ($0.10/1M tokens).
In conclusion, Mistral Small 3.1 24B Base is more expensive than Qwen3 235B A22B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 235B A22B has 211.0B more parameters than Mistral Small 3.1 24B Base, making it 879.2% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Mistral Small 3.1 24B Base supports multimodal inputs, whereas Qwen3 235B A22B does not.
Mistral Small 3.1 24B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Small 3.1 24B Base
Qwen3 235B A22B
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 Base was released on 2025-03-17, while Qwen3 235B A22B was released on 2025-04-29.
Qwen3 235B A22B is 1 month newer than Mistral Small 3.1 24B Base.
Mar 17, 2025
1.5 years ago
Apr 29, 2025
1.4 years ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Mistral Small 3.1 24B Base is available from Mistral AI. Qwen3 235B A22B is available from Fireworks, DeepInfra, Novita, Together.
Mistral Small 3.1 24B Base
Qwen3 235B A22B
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Small 3.1 24B Base and Qwen3 235B A22B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Small 3.1 24B Base vs Qwen3 235B A22B.