Mistral Small 3 vs Qwen2.5 Coder 32B Instruct
Mistral Small 3 and Qwen2.5 Coder 32B Instruct tie on the Artificial Analysis Intelligence Index at 6.7, and Mistral Small 3 costs 12.5x less per output token ($0.08 vs $1.00 per million). Updated October 21, 2026; 27 benchmarks have a result for both.
Mistral Small 3 or Qwen2.5 Coder 32B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Small 3 for output tokens 12.5x cheaper ($0.08 vs $1.00 per million) and work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 27
- Mistral Small 3 only
- 9
- Qwen2.5 Coder 32B Instruct only
- 8
- Like-for-like categories
- 6 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
Tied at 6.7.
Same board, both measured
Long documents
Listed context window
No call
Both take 33K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3
Mistral Small 3 $0.0001, Qwen2.5 Coder 32B Instruct $0.0012 per turn.
List prices
At a glance
- Coding index
- Mistral Small 3 not benchmarked, Qwen2.5 Coder 32B Instruct not benchmarked.
- Widest category
- Coding, 3.8 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena Text: legal and government: Mistral Small 3 1219 against Qwen2.5 Coder 32B Instruct 1257, 6.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Small 3 $0.08 against Qwen2.5 Coder 32B Instruct $1.00 per million output tokens, 12.5x apart.
- Context window
- Both take 33K tokens.
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 | Bars | Qwen2.5 Coder 32B Instruct | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 0 | 1 tie | |
| Reasoning | 2 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 3 | 2 | ||
| General | 5 | 6 | ||
| All shared boards | 10 | 16 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 16.4% | Only Qwen2.5 Coder 32B Instruct measured |
| SWE-bench Verified | Not measured | 47.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LiveCodeBench (Artificial Analysis run) | 25.2% | 29.5% | Qwen2.5 Coder 32B Instruct |
| LMArena Text: coding | 1246 | 1276 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: software and IT | 1248 | 1261 | Qwen2.5 Coder 32B Instruct |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index00
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 6.7 | Tie |
| Epoch Capabilities Index | Not measured | 119.5 | Only Qwen2.5 Coder 32B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 19.6% | Not measured | Only Mistral Small 3 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 46.2% | 41.7% | Mistral Small 3 |
| Humanity's Last Exam (Artificial Analysis run) | 3.8% | 3.5% | Mistral Small 3 |
| LMArena Text: hard prompts | 1233 | 1251 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: expert | 1202 | 1221 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: hard prompts in English | 1243 | 1269 | Qwen2.5 Coder 32B Instruct |
| Neither model has a result on the other 17 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Math Index | 4.3 | Not measured | Only Mistral Small 3 measured |
| AIME 2025 (Artificial Analysis run) | 4.3% | Not measured | Only Mistral Small 3 measured |
| GSM8K | Not measured | 93.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1240 | 1251 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: mathematical work | 1243 | 1243 | Qwen2.5 Coder 32B Instruct |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 65.2% | 63.5% | Mistral Small 3 |
| MMLU | Not measured | 79.1% | Only Qwen2.5 Coder 32B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 70.5% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: science | 1235 | 1221 | Mistral Small 3 |
| LMArena Text: medicine and healthcare | 1215 | 1187 | Mistral Small 3 |
| LMArena Text: legal and government | 1219 | 1257 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: business and finance | 1205 | 1224 | Qwen2.5 Coder 32B Instruct |
| Neither model has a result on the other 11 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index56
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| IFBench | 26.4% | Not measured | Only Mistral Small 3 measured |
| Long context reasoning (AA-LCR) | 0.0% | Not measured | Only Mistral Small 3 measured |
| HellaSwag | Not measured | 83.0% | Only Qwen2.5 Coder 32B Instruct measured |
| WinoGrande | Not measured | 80.8% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text | 1234 | 1230 | Mistral Small 3 |
| LMArena Text: instruction following | 1214 | 1223 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: creative writing | 1194 | 1174 | Mistral Small 3 |
| LMArena Text: English | 1256 | 1248 | Mistral Small 3 |
| LMArena Text: non-English | 1198 | 1205 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: Chinese | 1204 | 1222 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: German | 1211 | Not measured | Only Mistral Small 3 measured |
| LMArena Text: Japanese | 1111 | Not measured | Only Mistral Small 3 measured |
| LMArena Text: Korean | 1188 | Not measured | Only Mistral Small 3 measured |
| LMArena Text: French | 1204 | Not measured | Only Mistral Small 3 measured |
| LMArena Text: Russian | 1216 | 1228 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: multi-turn | 1217 | 1222 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: longer queries | 1246 | 1251 | Qwen2.5 Coder 32B Instruct |
| LMArena Text: writing and language | 1214 | 1191 | Mistral Small 3 |
| LMArena Text: entertainment and media | 1184 | 1150 | Mistral Small 3 |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 3 | Qwen2.5 Coder 32B Instruct | 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 costs less
Repository review
50K input + 3K output tokens
Mistral Small 3 costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3 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 | Qwen2.5 Coder 32B Instruct |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | January 30, 2025 | November 11, 2024 |
| Context window | 33K | 33K |
| Input $/Mtok | $0.05 | $0.66 |
| Output $/Mtok | $0.08 | $1.00 |
| 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 better than Qwen2.5 Coder 32B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Small 3 for output tokens 12.5x cheaper ($0.08 vs $1.00 per million) and work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, Mistral Small 3 or Qwen2.5 Coder 32B Instruct?
Mistral Small 3 costs $0.05 per million input tokens and $0.08 per million output tokens; Qwen2.5 Coder 32B Instruct costs $0.66 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Small 3 or Qwen2.5 Coder 32B Instruct?
Neither: both take 33K tokens.
How many benchmarks is the Mistral Small 3 vs Qwen2.5 Coder 32B Instruct comparison based on?
27 benchmarks have a result for both models as of October 21, 2026. Mistral Small 3's coding index rests on 0 independent benchmarks and Qwen2.5 Coder 32B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.