Mistral Small 3.1 24B vs Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 costs 1.9x less per output token than Mistral Small 3.1 24B ($0.30 vs $0.555 per million). Updated October 22, 2026; 28 benchmarks have a result for both.
Mistral Small 3.1 24B or Qwen3 30B A3B Instruct 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Small 3.1 24B for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 28
- Mistral Small 3.1 24B only
- 10
- Qwen3 30B A3B Instruct 2507 only
- 17
- Like-for-like categories
- 5 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 30B A3B Instruct 2507 has a AA Intelligence Index result, 7.5.
Directional only
Long documents
Listed context window
Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 30B A3B Instruct 2507
Mistral Small 3.1 24B $0.0006, Qwen3 30B A3B Instruct 2507 $0.0002 per turn.
List prices
At a glance
- Coding index
- Mistral Small 3.1 24B not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
- Widest category
- Math, 22.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: Chinese: Mistral Small 3.1 24B 1253 against Qwen3 30B A3B Instruct 2507 1432, 30.0 points apart on a 0 to 100 scale.
- Output price
- Mistral Small 3.1 24B $0.555 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 1.9x apart.
- Context window
- Mistral Small 3.1 24B takes 128K tokens, Qwen3 30B A3B 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 3.1 24B | Bars | Qwen3 30B A3B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 28 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 70.7% | Only Qwen3 30B A3B Instruct 2507 measured |
| SciCode | Not measured | 33.0% | Only Qwen3 30B A3B Instruct 2507 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 6.1% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: coding | 1309 | 1416 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: software and IT | 1301 | 1417 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 38 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 7.5 | Only Qwen3 30B A3B 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 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 28.1% | Only Qwen3 30B A3B Instruct 2507 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 41.4% | Only Qwen3 30B A3B Instruct 2507 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 70.7% | Only Qwen3 30B A3B Instruct 2507 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 10.3% | Only Qwen3 30B A3B Instruct 2507 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 55.6% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: hard prompts | 1278 | 1398 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: expert | 1257 | 1397 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: hard prompts in English | 1290 | 1406 | Qwen3 30B A3B Instruct 2507 |
| LMArena Vision: diagrams | 1119 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: homework | 1158 | Not measured | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 66.3 | Only Qwen3 30B A3B Instruct 2507 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 66.3% | Only Qwen3 30B A3B Instruct 2507 measured |
| OTIS Mock AIME | Not measured | 62.2% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: math | 1261 | 1394 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: mathematical work | 1271 | 1411 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 80.5% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: science | 1265 | 1393 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: medicine and healthcare | 1267 | 1392 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: legal and government | 1271 | 1387 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: business and finance | 1257 | 1389 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 15 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| IFBench | Not measured | 50.7% | Only Qwen3 30B A3B Instruct 2507 measured |
| Long context reasoning (AA-LCR) | Not measured | 61.3% | Only Qwen3 30B A3B Instruct 2507 measured |
| DTBench | Not measured | 67.2% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMCA | Not measured | 22.4% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text | 1277 | 1384 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: instruction following | 1263 | 1363 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: creative writing | 1252 | 1317 | Qwen3 30B A3B Instruct 2507 |
| LMArena Vision | 1136 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Text: English | 1295 | 1391 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: non-English | 1255 | 1372 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Chinese | 1253 | 1432 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: German | 1266 | 1379 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Japanese | 1208 | 1337 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Korean | 1207 | 1330 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: French | 1273 | 1419 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Spanish | 1284 | 1404 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Russian | 1263 | 1369 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Polish | 1242 | 1353 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: multi-turn | 1270 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: longer queries | 1299 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: writing and language | 1268 | 1336 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: entertainment and media | 1250 | 1334 | Qwen3 30B A3B Instruct 2507 |
| LMArena Vision: English | 1157 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: Chinese | 1155 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: reading text | 1132 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: humor | 1142 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: captioning | 1153 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: recognizing things | 1155 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: creative writing | 1123 | Not measured | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 3.1 24B | Qwen3 30B A3B 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
Qwen3 30B A3B Instruct 2507 costs less
Repository review
50K input + 3K output tokens
Qwen3 30B A3B Instruct 2507 costs less
Agent loop
200K input + 10K output tokens
Qwen3 30B A3B Instruct 2507 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 3.1 24B | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | March 17, 2025 | July 29, 2025 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.351 | $0.09 |
| Output $/Mtok | $0.555 | $0.30 |
| 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 3.1 24B better than Qwen3 30B A3B Instruct 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Small 3.1 24B for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Mistral Small 3.1 24B or Qwen3 30B A3B Instruct 2507?
Mistral Small 3.1 24B costs $0.351 per million input tokens and $0.555 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Small 3.1 24B or Qwen3 30B A3B Instruct 2507?
Qwen3 30B A3B Instruct 2507, with 262K tokens against 128K.
How many benchmarks is the Mistral Small 3.1 24B vs Qwen3 30B A3B Instruct 2507 comparison based on?
28 benchmarks have a result for both models as of October 22, 2026. Mistral Small 3.1 24B's coding index rests on 0 independent benchmarks and Qwen3 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.