Mistral Large 3 2512 vs Qwen3.5-Flash
Qwen3.5-Flash costs 5.8x less per output token than Mistral Large 3 2512 ($0.26 vs $1.50 per million). Updated October 22, 2026; 15 benchmarks have a result for both.
Mistral Large 3 2512 or Qwen3.5-Flash: which to pick
Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for work measured by CaseLaw (Vals AI) or TaxEval (Vals AI), where it leads.
- Shared results
- 15
- Mistral Large 3 2512 only
- 13
- Qwen3.5-Flash only
- 40
- 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
Only Qwen3.5-Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Mistral Large 3 2512 has a AA Intelligence Index result, 9.3.
Directional only
Agentic work
AA Agentic Index
No call
Only Mistral Large 3 2512 has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
Qwen3.5-Flash
Qwen3.5-Flash leads, 82.8% against 68.4%.
Same board, both measured
Math
AIME
Qwen3.5-Flash
Qwen3.5-Flash leads, 92.5% against 42.9%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.5-Flash
Qwen3.5-Flash leads, 84.1% against 79.8%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Large 3 2512 has a Design Arena: websites result, 1162.
Directional only
Long documents
Listed context window
Qwen3.5-Flash
Qwen3.5-Flash takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-Flash
Mistral Large 3 2512 $0.0013, Qwen3.5-Flash $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Qwen3.5-Flash
Mistral Large 3 2512 $0.77, Qwen3.5-Flash $0.40.
Published attempt cost and pass rate
At a glance
- Coding index
- Mistral Large 3 2512 not benchmarked, Qwen3.5-Flash 41.1 from 2 benchmarks.
- Widest category
- Math, 49.6 points apart on average over 1 shared benchmark.
- Widest single gap
- AIME: Mistral Large 3 2512 42.9% against Qwen3.5-Flash 92.5%, 49.6 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Qwen3.5-Flash $0.26 per million output tokens, 5.8x apart.
- Context window
- Mistral Large 3 2512 takes 262K tokens, Qwen3.5-Flash 1M.
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 3 2512 | Bars | Qwen3.5-Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 1 | ||
| Knowledge | 2 | 4 | ||
| General | 0 | 3 | ||
| All shared boards | 2 | 13 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1244 | Only Qwen3.5-Flash measured |
| AA Coding Index | 20.1 | Not measured | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Vals AI) | 55.3% | 83.3% | Qwen3.5-Flash |
| SWE-bench Verified (Vals AI) | 41.4% | 64.4% | Qwen3.5-Flash |
| ALE-Bench | 264.7 | 265.9 | Qwen3.5-Flash |
| LMArena Text: coding | Not measured | 1412 | Only Qwen3.5-Flash measured |
| LMArena Text: software and IT | Not measured | 1416 | Only Qwen3.5-Flash measured |
| LMArena WebDev: React | Not measured | 1229 | Only Qwen3.5-Flash measured |
| LMArena WebDev: HTML | Not measured | 1291 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | Not measured | Only Mistral Large 3 2512 measured |
| Epoch Capabilities Index | Not measured | 143.5 | Only Qwen3.5-Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 68.4% | 82.8% | Qwen3.5-Flash |
| MMMU Pro (Vals AI) | 66.2% | 81.9% | Qwen3.5-Flash |
| GPQA Diamond (Epoch AI run) | Not measured | 82.3% | Only Qwen3.5-Flash measured |
| Chess puzzles | Not measured | 14.0% | Only Qwen3.5-Flash measured |
| Mystery game puzzles | Not measured | 20.0% | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts | Not measured | 1403 | Only Qwen3.5-Flash measured |
| LMArena Text: expert | Not measured | 1407 | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1409 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AIME | 42.9% | 92.5% | Qwen3.5-Flash |
| MGSM (Vals AI) | 85.4% | Not measured | Only Mistral Large 3 2512 measured |
| OTIS Mock AIME | Not measured | 84.4% | Only Qwen3.5-Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 18.2% | Only Qwen3.5-Flash measured |
| LMArena Text: math | Not measured | 1407 | Only Qwen3.5-Flash measured |
| LMArena Text: mathematical work | Not measured | 1413 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| MMLU Pro | 79.8% | 84.1% | Qwen3.5-Flash |
| LegalBench (Vals AI) | 79.1% | 84.3% | Qwen3.5-Flash |
| CaseLaw (Vals AI) | 61.4% | 56.0% | Mistral Large 3 2512 |
| CorpFin (Vals AI) | 61.0% | 63.6% | Qwen3.5-Flash |
| TaxEval (Vals AI) | 73.1% | 72.2% | Mistral Large 3 2512 |
| MortgageTax (Vals AI) | 52.1% | 67.4% | Qwen3.5-Flash |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| MedCode (Vals AI) | Not measured | 33.0% | Only Qwen3.5-Flash measured |
| SimpleQA Verified | Not measured | 20.3% | Only Qwen3.5-Flash measured |
| LMArena Text: science | Not measured | 1415 | Only Qwen3.5-Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1407 | Only Qwen3.5-Flash measured |
| LMArena Text: legal and government | Not measured | 1398 | Only Qwen3.5-Flash measured |
| LMArena Text: business and finance | Not measured | 1394 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: UI components | 1099 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: game dev | 1079 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: data viz | 1137 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: 3D | 1099 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: all code categories | 1141 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: SVG | 992 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: ASCII art | 1069 | Not measured | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Large 3 2512 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 24.6% | 42.5% | Qwen3.5-Flash |
| MedScribe (Vals AI) | Not measured | 70.6% | Only Qwen3.5-Flash measured |
| DTBench | 65.1% | 82.9% | Qwen3.5-Flash |
| LMCA | 16.7% | 29.1% | Qwen3.5-Flash |
| LMArena Text | Not measured | 1397 | Only Qwen3.5-Flash measured |
| LMArena Text: instruction following | Not measured | 1374 | Only Qwen3.5-Flash measured |
| LMArena Text: creative writing | Not measured | 1343 | Only Qwen3.5-Flash measured |
| LMArena Text: English | Not measured | 1404 | Only Qwen3.5-Flash measured |
| LMArena Text: non-English | Not measured | 1385 | Only Qwen3.5-Flash measured |
| LMArena Text: Chinese | Not measured | 1445 | Only Qwen3.5-Flash measured |
| LMArena Text: German | Not measured | 1390 | Only Qwen3.5-Flash measured |
| LMArena Text: Japanese | Not measured | 1369 | Only Qwen3.5-Flash measured |
| LMArena Text: Korean | Not measured | 1344 | Only Qwen3.5-Flash measured |
| LMArena Text: French | Not measured | 1413 | Only Qwen3.5-Flash measured |
| LMArena Text: Spanish | Not measured | 1400 | Only Qwen3.5-Flash measured |
| LMArena Text: Russian | Not measured | 1380 | Only Qwen3.5-Flash measured |
| LMArena Text: Polish | Not measured | 1376 | Only Qwen3.5-Flash measured |
| LMArena Text: multi-turn | Not measured | 1393 | Only Qwen3.5-Flash measured |
| LMArena Text: longer queries | Not measured | 1392 | Only Qwen3.5-Flash measured |
| LMArena Text: writing and language | Not measured | 1369 | Only Qwen3.5-Flash measured |
| LMArena Text: entertainment and media | Not measured | 1347 | Only Qwen3.5-Flash measured |
| 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 Large 3 2512 | Qwen3.5-Flash | 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
Qwen3.5-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-Flash 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 3 2512 | Qwen3.5-Flash |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | December 1, 2025 | February 25, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.50 | $0.065 |
| Output $/Mtok | $1.50 | $0.26 |
| Coding index | Not benchmarked | 41.1 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.77 | $0.40 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Qwen3.5-Flash for coding?
Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for work measured by CaseLaw (Vals AI) or TaxEval (Vals AI), where it leads.
Which is cheaper, Mistral Large 3 2512 or Qwen3.5-Flash?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Per solved SWE-bench Verified task, Mistral Large 3 2512 costs $0.77 and Qwen3.5-Flash $0.40.
Which has the bigger context window, Mistral Large 3 2512 or Qwen3.5-Flash?
Qwen3.5-Flash, with 1M tokens against 262K.
How many benchmarks is the Mistral Large 3 2512 vs Qwen3.5-Flash comparison based on?
15 benchmarks have a result for both models as of October 22, 2026. Mistral Large 3 2512's coding index rests on 1 independent benchmark and Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.