Mistral Small 3.2 24B vs Qwen3 235B A22B Instruct 2507
Mistral Small 3.2 24B costs 2.6x less per output token than Qwen3 235B A22B Instruct 2507 ($0.30 vs $0.775 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Mistral Small 3.2 24B or Qwen3 235B A22B Instruct 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Small 3.2 24B for output tokens 2.6x cheaper ($0.30 vs $0.775 per million) and work measured by Design Arena: websites or Design Arena: UI components, where it leads.
- Shared results
- 5
- Mistral Small 3.2 24B only
- 0
- Qwen3 235B A22B Instruct 2507 only
- 19
- Like-for-like categories
- 1 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3 235B A22B Instruct 2507 has a AA Intelligence Index result, 12.0.
Directional only
Web design
Design Arena: websites
Qwen3 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 leads, 1058 against 896.
Same board, both measured
Long documents
Listed context window
Qwen3 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 takes 262K tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.2 24B
Mistral Small 3.2 24B $0.0003, Qwen3 235B A22B Instruct 2507 $0.0005 per turn.
List prices
At a glance
- Coding index
- Mistral Small 3.2 24B not benchmarked, Qwen3 235B A22B Instruct 2507 not benchmarked.
- Widest category
- Web design, 13.9 points apart on average over 5 shared benchmarks.
- Widest single gap
- Design Arena: websites: Mistral Small 3.2 24B 896 against Qwen3 235B A22B Instruct 2507 1058, 20.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Small 3.2 24B $0.30 against Qwen3 235B A22B Instruct 2507 $0.775 per million output tokens, 2.6x apart.
- Context window
- Mistral Small 3.2 24B takes 256K tokens, Qwen3 235B A22B Instruct 2507 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Mistral Small 3.2 24B | Bars | Qwen3 235B A22B Instruct 2507 | Ties |
|---|---|---|---|---|
| Web design | 0 | 5 | ||
| All shared boards | 0 | 5 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.8% | Only Qwen3 235B A22B Instruct 2507 measured |
| SciCode | Not measured | 41.4% | Only Qwen3 235B A22B Instruct 2507 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 15.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| WeirdML | Not measured | 38.7% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.0 | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 53.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 52.1% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 79.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 15.9% | Only Qwen3 235B A22B Instruct 2507 measured |
| ARC-AGI | Not measured | 11.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| ARC-AGI-2 | Not measured | 1.3% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 91.0 | Only Qwen3 235B A22B Instruct 2507 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 91.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 84.3% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 19 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | 896 | 1058 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: UI components | 904 | 963 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: game dev | 889 | 951 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: data viz | 929 | 1070 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: 3D | Not measured | 994 | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: all code categories | 907 | 1038 | Qwen3 235B A22B Instruct 2507 |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| IFBench | Not measured | 51.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| Long context reasoning (AA-LCR) | Not measured | 72.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| DTBench | Not measured | 78.4% | Only Qwen3 235B A22B Instruct 2507 measured |
| LMCA | Not measured | 23.5% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Small 3.2 24B costs less
Repository review
50K input + 3K output tokens
Mistral Small 3.2 24B costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3.2 24B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Mistral Small 3.2 24B | Qwen3 235B A22B Instruct 2507 |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | June 20, 2025 | July 21, 2025 |
| Context window | 256K | 262K |
| Input $/Mtok | $0.10 | $0.145 |
| Output $/Mtok | $0.30 | $0.775 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Small 3.2 24B better than Qwen3 235B A22B Instruct 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Small 3.2 24B for output tokens 2.6x cheaper ($0.30 vs $0.775 per million) and work measured by Design Arena: websites or Design Arena: UI components, where it leads.
Which is cheaper, Mistral Small 3.2 24B or Qwen3 235B A22B Instruct 2507?
Mistral Small 3.2 24B costs $0.10 per million input tokens and $0.30 per million output tokens; Qwen3 235B A22B Instruct 2507 costs $0.145 and $0.775. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Small 3.2 24B or Qwen3 235B A22B Instruct 2507?
Qwen3 235B A22B Instruct 2507, with 262K tokens against 256K.
How many benchmarks is the Mistral Small 3.2 24B vs Qwen3 235B A22B Instruct 2507 comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Mistral Small 3.2 24B's coding index rests on 0 independent benchmarks and Qwen3 235B A22B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.