Devstral 2 2512 vs Qwen3 30B A3B Instruct 2507
Devstral 2 2512 leads Qwen3 30B A3B Instruct 2507 on the Artificial Analysis Intelligence Index, 8.6 to 7.5, and Qwen3 30B A3B Instruct 2507 costs 6.7x less per output token ($0.30 vs $2.00 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
Devstral 2 2512 or Qwen3 30B A3B Instruct 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 1
- Devstral 2 2512 only
- 5
- Qwen3 30B A3B Instruct 2507 only
- 44
- Like-for-like categories
- 1 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
Devstral 2 2512
Devstral 2 2512 leads, 8.6 against 7.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Devstral 2 2512 has a AA Agentic Index result, 2.3.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 30B A3B Instruct 2507
Devstral 2 2512 $0.0014, Qwen3 30B A3B Instruct 2507 $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Devstral 2 2512 has the number, $1.19.
Directional only
At a glance
- Coding index
- Devstral 2 2512 not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
- Widest category
- Intelligence, 1.1 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: Devstral 2 2512 8.6 against Qwen3 30B A3B Instruct 2507 7.5, 1.1 points apart on a 0 to 100 scale.
- Output price
- Devstral 2 2512 $2.00 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 6.7x apart.
- Context window
- Both take 262K 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 | Devstral 2 2512 | Bars | Qwen3 30B A3B Instruct 2507 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards, none shared
| Benchmark | Devstral 2 2512 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.8% | Not measured | Only Devstral 2 2512 measured |
| AA Coding Index | 31.3 | Not measured | Only Devstral 2 2512 measured |
| LiveCodeBench (Vals AI) | 51.8% | Not measured | Only Devstral 2 2512 measured |
| SWE-bench Verified (Vals AI) | 62.8% | Not measured | Only Devstral 2 2512 measured |
| 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 | 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 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Devstral 2 2512 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 8.6 | 7.5 | Devstral 2 2512 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Devstral 2 2512 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Agentic Index | 2.3 | Not measured | Only Devstral 2 2512 measured |
| 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 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Devstral 2 2512 | 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 | 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 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Devstral 2 2512 | 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 | 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 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Devstral 2 2512 | 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 | 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 13 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Devstral 2 2512 | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | Devstral 2 2512 | 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 | 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 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Devstral 2 2512 | 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 Devstral 2 2512 | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | December 9, 2025 | July 29, 2025 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.40 | $0.09 |
| Output $/Mtok | $2.00 | $0.30 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $1.19 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Devstral 2 2512 better than Qwen3 30B A3B Instruct 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Devstral 2 2512 or Qwen3 30B A3B Instruct 2507?
Devstral 2 2512 costs $0.40 per million input tokens and $2.00 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for Devstral 2 2512 only.
Which has the bigger context window, Devstral 2 2512 or Qwen3 30B A3B Instruct 2507?
Neither: both take 262K tokens.
How many benchmarks is the Devstral 2 2512 vs Qwen3 30B A3B Instruct 2507 comparison based on?
1 benchmarks have a result for both models as of October 21, 2026. Devstral 2 2512's coding index rests on 1 independent benchmark 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.