Mistral Large vs Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 leads Mistral Large on the Artificial Analysis Intelligence Index, 7.5 to 5.8, and Qwen3 30B A3B Instruct 2507 costs 20.0x less per output token ($0.30 vs $6.00 per million). Updated October 22, 2026; 34 benchmarks have a result for both.
Mistral Large 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 Large for work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 34
- Mistral Large only
- 10
- Qwen3 30B A3B Instruct 2507 only
- 11
- 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
Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 leads, 7.5 against 5.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
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 Large $0.0050, Qwen3 30B A3B Instruct 2507 $0.0002 per turn.
List prices
At a glance
- Coding index
- Mistral Large not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
- Widest category
- Coding, 33.4 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveCodeBench (Artificial Analysis run): Mistral Large 17.8% against Qwen3 30B A3B Instruct 2507 70.7%, 52.9 points apart on a 0 to 100 scale.
- Output price
- Mistral Large $6.00 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 20.0x apart.
- Context window
- Mistral Large 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 Large | Bars | Qwen3 30B A3B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 5 | ||
| General | 0 | 18 | ||
| All shared boards | 0 | 34 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Mistral Large | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 37.1% | Not measured | Only Mistral Large measured |
| LiveCodeBench (Artificial Analysis run) | 17.8% | 70.7% | Qwen3 30B A3B Instruct 2507 |
| 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 | 1275 | 1416 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: software and IT | 1274 | 1417 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.8 | 7.5 | Qwen3 30B A3B Instruct 2507 |
| Epoch Capabilities Index | 122.1 | Not measured | Only Mistral Large measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Large | 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 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mistral Large | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond | 47.7% | Not measured | Only Mistral Large measured |
| GPQA Diamond (Artificial Analysis run) | 35.1% | 70.7% | Qwen3 30B A3B Instruct 2507 |
| Humanity's Last Exam (Artificial Analysis run) | 3.5% | 10.3% | Qwen3 30B A3B Instruct 2507 |
| GPQA Diamond (Epoch AI run) | Not measured | 55.6% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: hard prompts | 1257 | 1398 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: expert | 1208 | 1397 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: hard prompts in English | 1268 | 1406 | Qwen3 30B A3B Instruct 2507 |
| 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 Large | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AIME | 9.2% | Not measured | Only Mistral Large measured |
| MATH 500 (Vals AI) | 74.4% | Not measured | Only Mistral Large measured |
| MGSM (Vals AI) | 87.2% | Not measured | Only Mistral Large measured |
| 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 | 1257 | 1411 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mistral Large | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| MMLU Pro | 69.7% | Not measured | Only Mistral Large measured |
| TaxEval (Vals AI) | 63.8% | Not measured | Only Mistral Large measured |
| MedQA (Vals AI) | 76.2% | Not measured | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | 51.5% | 80.5% | Qwen3 30B A3B Instruct 2507 |
| MMLU | 68.8% | Not measured | Only Mistral Large measured |
| LMArena Text: science | 1260 | 1393 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: medicine and healthcare | 1255 | 1392 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: legal and government | 1275 | 1387 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: business and finance | 1238 | 1389 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 9 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | 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 index018
| Benchmark | Mistral Large | 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 | 60.8% | 67.2% | Qwen3 30B A3B Instruct 2507 |
| LMCA | Not measured | 22.4% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text | 1265 | 1384 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: instruction following | 1249 | 1363 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: creative writing | 1242 | 1317 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: English | 1284 | 1391 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: non-English | 1235 | 1372 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Chinese | 1239 | 1432 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: German | 1242 | 1379 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Japanese | 1170 | 1337 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Korean | 1202 | 1330 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: French | 1325 | 1419 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Spanish | 1268 | 1404 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Russian | 1252 | 1369 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Polish | 1157 | 1353 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: multi-turn | 1260 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: longer queries | 1261 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: writing and language | 1261 | 1336 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: entertainment and media | 1230 | 1334 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | 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 Large | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | February 26, 2024 | July 29, 2025 |
| Context window | 128K | 262K |
| Input $/Mtok | $2.00 | $0.09 |
| Output $/Mtok | $6.00 | $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 Large 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 Large for work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, Mistral Large or Qwen3 30B A3B Instruct 2507?
Mistral Large costs $2.00 per million input tokens and $6.00 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 Large or Qwen3 30B A3B Instruct 2507?
Qwen3 30B A3B Instruct 2507, with 262K tokens against 128K.
How many benchmarks is the Mistral Large vs Qwen3 30B A3B Instruct 2507 comparison based on?
34 benchmarks have a result for both models as of October 22, 2026. Mistral Large'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.