Mistral Large 2407 vs Qwen3 30B A3B Instruct 2507
Mistral Large 2407 leads Qwen3 30B A3B Instruct 2507 on the Artificial Analysis Intelligence Index, 7.6 to 7.5, and Qwen3 30B A3B Instruct 2507 costs 20.0x less per output token ($0.30 vs $6.00 per million). Updated October 22, 2026; 13 benchmarks have a result for both.
Mistral Large 2407 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 2407 for work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 13
- Mistral Large 2407 only
- 4
- Qwen3 30B A3B Instruct 2507 only
- 32
- Like-for-like categories
- 7 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
Mistral Large 2407
Mistral Large 2407 leads, 7.6 against 7.5.
Same board, both measured
Long documents
Listed context window
Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 30B A3B Instruct 2507
Mistral Large 2407 $0.0050, Qwen3 30B A3B Instruct 2507 $0.0002 per turn.
List prices
At a glance
- Coding index
- Mistral Large 2407 not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
- Widest category
- Math, 62.1 points apart on average over 3 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): Mistral Large 2407 0.0% against Qwen3 30B A3B Instruct 2507 66.3%, 66.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 2407 $6.00 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 20.0x apart.
- Context window
- Mistral Large 2407 takes 131K 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 2407 | Bars | Qwen3 30B A3B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 3 | ||
| All shared boards | 2 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Mistral Large 2407 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 26.7% | 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 | Not measured | 1416 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: software and IT | Not measured | 1417 | Only Qwen3 30B A3B Instruct 2507 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 2407 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.6 | 7.5 | Mistral Large 2407 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 2407 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 33.0% | 28.1% | Mistral Large 2407 |
| 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 index03
| Benchmark | Mistral Large 2407 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 47.2% | 70.7% | Qwen3 30B A3B Instruct 2507 |
| Humanity's Last Exam (Artificial Analysis run) | 2.9% | 10.3% | Qwen3 30B A3B Instruct 2507 |
| GPQA Diamond (Epoch AI run) | 49.0% | 55.6% | Qwen3 30B A3B Instruct 2507 |
| SimpleBench | 22.5% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text: hard prompts | Not measured | 1398 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: expert | Not measured | 1397 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: hard prompts in English | Not measured | 1406 | Only Qwen3 30B A3B Instruct 2507 measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Large 2407 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Math Index | 0.0 | 66.3 | Qwen3 30B A3B Instruct 2507 |
| AIME 2025 (Artificial Analysis run) | 0.0% | 66.3% | Qwen3 30B A3B Instruct 2507 |
| OTIS Mock AIME | 8.5% | 62.2% | Qwen3 30B A3B Instruct 2507 |
| MATH level 5 | 44.8% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text: math | Not measured | 1394 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: mathematical work | Not measured | 1411 | Only Qwen3 30B A3B Instruct 2507 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 2407 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 68.3% | 80.5% | Qwen3 30B A3B Instruct 2507 |
| MMLU | 80.0% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text: science | Not measured | 1393 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: medicine and healthcare | Not measured | 1392 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: legal and government | Not measured | 1387 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: business and finance | Not measured | 1389 | Only Qwen3 30B A3B Instruct 2507 measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 2407 | 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 index03
| Benchmark | Mistral Large 2407 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| IFBench | 31.6% | 50.7% | Qwen3 30B A3B Instruct 2507 |
| Long context reasoning (AA-LCR) | 2.0% | 61.3% | Qwen3 30B A3B Instruct 2507 |
| DTBench | 61.2% | 67.2% | Qwen3 30B A3B Instruct 2507 |
| LMCA | Not measured | 22.4% | Only Qwen3 30B A3B Instruct 2507 measured |
| Creative writing (Lech Mazur) | 69.0% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text | Not measured | 1384 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: instruction following | Not measured | 1363 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: creative writing | Not measured | 1317 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: English | Not measured | 1391 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: non-English | Not measured | 1372 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Chinese | Not measured | 1432 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: German | Not measured | 1379 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Japanese | Not measured | 1337 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Korean | Not measured | 1330 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: French | Not measured | 1419 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Spanish | Not measured | 1404 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Russian | Not measured | 1369 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Polish | Not measured | 1353 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: multi-turn | Not measured | 1378 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: longer queries | Not measured | 1378 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: writing and language | Not measured | 1336 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: entertainment and media | Not measured | 1334 | Only Qwen3 30B A3B Instruct 2507 measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 2407 | 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 2407 | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | November 19, 2024 | July 29, 2025 |
| Context window | 131K | 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 2407 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 2407 for work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, Mistral Large 2407 or Qwen3 30B A3B Instruct 2507?
Mistral Large 2407 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 2407 or Qwen3 30B A3B Instruct 2507?
Qwen3 30B A3B Instruct 2507, with 262K tokens against 131K.
How many benchmarks is the Mistral Large 2407 vs Qwen3 30B A3B Instruct 2507 comparison based on?
13 benchmarks have a result for both models as of October 22, 2026. Mistral Large 2407'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.