Mistral Small 3.2 24B vs Qwen-Plus
Mistral Small 3.2 24B costs 2.6x less per output token than Qwen-Plus ($0.30 vs $0.78 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.30
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.78
Mistral Small 3.2 24B or Qwen-Plus: 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 $0.78 per million).
No benchmark has tested both yet. Mistral Small 3.2 24B has results on Design Arena: websites, Design Arena: UI components and Design Arena: game dev; Qwen-Plus on LMArena Text: coding, LMArena Text: software and IT and GPQA Diamond (Epoch AI run). Compare them on price and context instead.
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
Web design
Design Arena: websites
No call
Only Mistral Small 3.2 24B has a Design Arena: websites result, 896.
Directional only
Long documents
Listed context window
Qwen-Plus
Qwen-Plus takes 1M 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, Qwen-Plus $0.0006 per turn.
List prices
At a glance
- Coding index
- Mistral Small 3.2 24B not benchmarked, Qwen-Plus not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Mistral Small 3.2 24B $0.30 against Qwen-Plus $0.78 per million output tokens, 2.6x apart.
- Context window
- Mistral Small 3.2 24B takes 256K tokens, Qwen-Plus 1M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards measured
| Benchmark | Mistral Small 3.2 24B | Qwen-Plus | Leader |
|---|---|---|---|
| LMArena Text: coding | Not measured | 1328 | Only Qwen-Plus measured |
| LMArena Text: software and IT | Not measured | 1343 | Only Qwen-Plus measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Mistral Small 3.2 24B | Qwen-Plus | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | Not measured | 48.1% | Only Qwen-Plus measured |
| LMArena Text: hard prompts | Not measured | 1317 | Only Qwen-Plus measured |
| LMArena Text: expert | Not measured | 1328 | Only Qwen-Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1333 | Only Qwen-Plus measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Mistral Small 3.2 24B | Qwen-Plus | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 17.8% | Only Qwen-Plus measured |
| MATH level 5 | Not measured | 65.3% | Only Qwen-Plus measured |
| LMArena Text: math | Not measured | 1326 | Only Qwen-Plus measured |
| LMArena Text: mathematical work | Not measured | 1332 | Only Qwen-Plus measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Mistral Small 3.2 24B | Qwen-Plus | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1352 | Only Qwen-Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1350 | Only Qwen-Plus measured |
| LMArena Text: legal and government | Not measured | 1349 | Only Qwen-Plus measured |
| LMArena Text: business and finance | Not measured | 1303 | Only Qwen-Plus measured |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Mistral Small 3.2 24B | Qwen-Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 896 | Not measured | Only Mistral Small 3.2 24B measured |
| Design Arena: UI components | 907 | Not measured | Only Mistral Small 3.2 24B measured |
| Design Arena: game dev | 888 | Not measured | Only Mistral Small 3.2 24B measured |
| Design Arena: data viz | 929 | Not measured | Only Mistral Small 3.2 24B measured |
| Design Arena: all code categories | 907 | Not measured | Only Mistral Small 3.2 24B measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index14 boards measured
| Benchmark | Mistral Small 3.2 24B | Qwen-Plus | Leader |
|---|---|---|---|
| DTBench | Not measured | 81.1% | Only Qwen-Plus measured |
| LMCA | Not measured | 24.0% | Only Qwen-Plus measured |
| LMArena Text | Not measured | 1326 | Only Qwen-Plus measured |
| LMArena Text: instruction following | Not measured | 1303 | Only Qwen-Plus measured |
| LMArena Text: creative writing | Not measured | 1292 | Only Qwen-Plus measured |
| LMArena Text: English | Not measured | 1339 | Only Qwen-Plus measured |
| LMArena Text: non-English | Not measured | 1310 | Only Qwen-Plus measured |
| LMArena Text: Chinese | Not measured | 1347 | Only Qwen-Plus measured |
| LMArena Text: Japanese | Not measured | 1251 | Only Qwen-Plus measured |
| LMArena Text: Russian | Not measured | 1323 | Only Qwen-Plus measured |
| LMArena Text: multi-turn | Not measured | 1336 | Only Qwen-Plus measured |
| LMArena Text: longer queries | Not measured | 1324 | Only Qwen-Plus measured |
| LMArena Text: writing and language | Not measured | 1296 | Only Qwen-Plus measured |
| LMArena Text: entertainment and media | Not measured | 1270 | Only Qwen-Plus measured |
| Neither model has a result on the other 32 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 | Qwen-Plus |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | No public weights listed |
| Released | June 20, 2025 | February 1, 2025 |
| Context window | 256K | 1M |
| Input $/Mtok | $0.10 | $0.26 |
| Output $/Mtok | $0.30 | $0.78 |
| 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 Qwen-Plus 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 $0.78 per million).
Which is cheaper, Mistral Small 3.2 24B or Qwen-Plus?
Mistral Small 3.2 24B costs $0.10 per million input tokens and $0.30 per million output tokens; Qwen-Plus costs $0.26 and $0.78. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Small 3.2 24B or Qwen-Plus?
Qwen-Plus, with 1M tokens against 256K.
Has any benchmark tested both Mistral Small 3.2 24B and Qwen-Plus?
No benchmark has tested both yet. Mistral Small 3.2 24B has results on Design Arena: websites, Design Arena: UI components and Design Arena: game dev; Qwen-Plus on LMArena Text: coding, LMArena Text: software and IT and GPQA Diamond (Epoch AI run). Compare them on price and context instead. Data as of October 21, 2026.