Mistral Medium 3.5 vs Qwen3.5-122B-A10B
Updated October 21, 2026. 49 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3.5-122B-A10B for coding: it scores 22.9 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5.
Pick Mistral Medium 3.5 when what matters is AA Coding Index or SciCode, where it leads.
- Shared results
- 49
- Mistral Medium 3.5 only
- 31
- Qwen3.5-122B-A10B only
- 2
- Like-for-like categories
- 7 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Qwen3.5-122B-A10B
Qwen3.5-122B-A10B scores 22.9 against 9.2.
One benchmark behind each score
Intelligence
AA Intelligence Index
Qwen3.5-122B-A10B
Qwen3.5-122B-A10B leads, 17.7 against 14.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.5 has a AA Agentic Index result, 7.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Medium 3.5 has a GPQA Diamond result, 34.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.5 has a MMLU Pro result, 75.3%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Medium 3.5 has a Design Arena: websites result, 1142.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-122B-A10B
Mistral Medium 3.5 $0.0053, Qwen3.5-122B-A10B $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Medium 3.5 has the number, $6.02.
Directional only
At a glance
- Coding index
- Mistral Medium 3.5 9.2 from 1 benchmark, Qwen3.5-122B-A10B 22.9 from 1 benchmark.
- Widest category
- Coding, 6.5 points apart on average over 8 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Mistral Medium 3.5 1254 against Qwen3.5-122B-A10B 1353, 16.4 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.5 $7.50 against Qwen3.5-122B-A10B $2.08 per million output tokens, 3.6x 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 | Mistral Medium 3.5 | Bars | Qwen3.5-122B-A10B | Ties |
|---|---|---|---|---|
| Coding | 5 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 4 | 3 | ||
| Math | 1 | 1 | ||
| Knowledge | 2 | 2 | ||
| General | 12 | 14 | ||
| All shared boards | 25 | 24 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index53
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| LMArena WebDev | 1264 | 1361 | Qwen3.5-122B-A10B |
| AA Coding Index | 46.9 | 43.3 | Mistral Medium 3.5 |
| SWE-bench Verified (Vals AI) | 66.4% | Not measured | Only Mistral Medium 3.5 measured |
| Vibe Code Bench (Vals AI) | 2.9% | Not measured | Only Mistral Medium 3.5 measured |
| Code migration (Vals AI) | 5.1% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 39.0% | Not measured | Only Mistral Medium 3.5 measured |
| SciCode | 40.2% | 39.7% | Mistral Medium 3.5 |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 31.1% | Mistral Medium 3.5 |
| ALE-Bench | 764.0 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: coding | 1460 | 1436 | Mistral Medium 3.5 |
| LMArena Text: software and IT | 1458 | 1436 | Mistral Medium 3.5 |
| LMArena WebDev: React | 1254 | 1353 | Qwen3.5-122B-A10B |
| LMArena WebDev: HTML | 1308 | 1351 | Qwen3.5-122B-A10B |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.2 | 17.7 | Qwen3.5-122B-A10B |
| Epoch Capabilities Index | 141.4 | Not measured | Only Mistral Medium 3.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| AA Agentic Index | 7.0 | Not measured | Only Mistral Medium 3.5 measured |
| Finance Agent (Vals AI) | 32.1% | Not measured | Only Mistral Medium 3.5 measured |
| Tax Agent Bench (Vals AI) | 4.5% | Not measured | Only Mistral Medium 3.5 measured |
| Legal Research Bench (Vals AI) | 9.1% | Not measured | Only Mistral Medium 3.5 measured |
| Excel Modeling Benchmark (Vals AI) | 11.2% | Not measured | Only Mistral Medium 3.5 measured |
| τ²-Bench Telecom | 94.2% | 93.6% | Mistral Medium 3.5 |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index43
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| GPQA Diamond | 34.9% | Not measured | Only Mistral Medium 3.5 measured |
| GPQA Diamond (Artificial Analysis run) | 74.8% | 85.7% | Qwen3.5-122B-A10B |
| Humanity's Last Exam (Artificial Analysis run) | 13.8% | 25.2% | Qwen3.5-122B-A10B |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.5-122B-A10B measured |
| LMArena Text: hard prompts | 1436 | 1421 | Mistral Medium 3.5 |
| LMArena Text: expert | 1432 | 1431 | Mistral Medium 3.5 |
| LMArena Text: hard prompts in English | 1445 | 1431 | Mistral Medium 3.5 |
| LMArena Vision: diagrams | 1254 | 1249 | Mistral Medium 3.5 |
| LMArena Vision: homework | 1230 | 1261 | Qwen3.5-122B-A10B |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: math | 1431 | 1431 | Qwen3.5-122B-A10B |
| LMArena Text: mathematical work | 1440 | 1431 | Mistral Medium 3.5 |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | Not measured | Only Mistral Medium 3.5 measured |
| CaseLaw (Vals AI) | 44.2% | Not measured | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | 58.8% | Not measured | Only Mistral Medium 3.5 measured |
| TaxEval (Vals AI) | 68.0% | Not measured | Only Mistral Medium 3.5 measured |
| MortgageTax (Vals AI) | 28.9% | Not measured | Only Mistral Medium 3.5 measured |
| MedCode (Vals AI) | 33.8% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: science | 1428 | 1432 | Qwen3.5-122B-A10B |
| LMArena Text: medicine and healthcare | 1409 | 1423 | Qwen3.5-122B-A10B |
| LMArena Text: legal and government | 1437 | 1422 | Mistral Medium 3.5 |
| LMArena Text: business and finance | 1426 | 1414 | Mistral Medium 3.5 |
| 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 Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| Design Arena: websites | 1142 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: UI components | 1079 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: game dev | 1079 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: data viz | 1120 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | 1061 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | 1122 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: SVG | 949 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | 1062 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index1214
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 37.6% | Not measured | Only Mistral Medium 3.5 measured |
| MedScribe (Vals AI) | 67.7% | Not measured | Only Mistral Medium 3.5 measured |
| Vals Multimodal Index | 34.8% | Not measured | Only Mistral Medium 3.5 measured |
| IFBench | 68.8% | 75.7% | Qwen3.5-122B-A10B |
| Long context reasoning (AA-LCR) | 69.3% | 76.3% | Qwen3.5-122B-A10B |
| DTBench | 75.5% | 84.3% | Qwen3.5-122B-A10B |
| LMCA | 26.1% | 32.2% | Qwen3.5-122B-A10B |
| Surface Evolver Bench | 26.9% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text | 1421 | 1417 | Mistral Medium 3.5 |
| LMArena Text: instruction following | 1415 | 1399 | Mistral Medium 3.5 |
| LMArena Text: creative writing | 1374 | 1368 | Mistral Medium 3.5 |
| LMArena Vision | 1222 | 1244 | Qwen3.5-122B-A10B |
| LMArena Text: English | 1433 | 1428 | Mistral Medium 3.5 |
| LMArena Text: non-English | 1404 | 1401 | Mistral Medium 3.5 |
| LMArena Text: Chinese | 1444 | 1463 | Qwen3.5-122B-A10B |
| LMArena Text: German | 1453 | 1425 | Mistral Medium 3.5 |
| LMArena Text: Japanese | Not measured | 1367 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Korean | 1384 | 1353 | Mistral Medium 3.5 |
| LMArena Text: French | 1448 | 1443 | Mistral Medium 3.5 |
| LMArena Text: Spanish | 1411 | 1425 | Qwen3.5-122B-A10B |
| LMArena Text: Russian | 1395 | 1400 | Qwen3.5-122B-A10B |
| LMArena Text: Polish | 1430 | 1398 | Mistral Medium 3.5 |
| LMArena Text: multi-turn | 1423 | 1416 | Mistral Medium 3.5 |
| LMArena Text: longer queries | 1415 | 1410 | Mistral Medium 3.5 |
| LMArena Text: writing and language | 1384 | 1387 | Qwen3.5-122B-A10B |
| LMArena Text: entertainment and media | 1382 | 1366 | Mistral Medium 3.5 |
| LMArena Vision: English | 1240 | 1249 | Qwen3.5-122B-A10B |
| LMArena Vision: Chinese | 1244 | 1301 | Qwen3.5-122B-A10B |
| LMArena Vision: reading text | 1233 | 1251 | Qwen3.5-122B-A10B |
| LMArena Vision: humor | 1216 | 1243 | Qwen3.5-122B-A10B |
| LMArena Vision: creative writing | 1198 | 1220 | Qwen3.5-122B-A10B |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Medium 3.5 | Qwen3.5-122B-A10B | 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
Qwen3.5-122B-A10B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-122B-A10B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-122B-A10B 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 Medium 3.5 | Qwen3.5-122B-A10B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | April 30, 2026 | February 25, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $1.50 | $0.26 |
| Output $/Mtok | $7.50 | $2.08 |
| Coding index | 9.2 | 22.9 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $6.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than Qwen3.5-122B-A10B for coding?
Pick Qwen3.5-122B-A10B for coding: it scores 22.9 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5. Pick Mistral Medium 3.5 when what matters is AA Coding Index or SciCode, where it leads.
Which is cheaper, Mistral Medium 3.5 or Qwen3.5-122B-A10B?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, Mistral Medium 3.5 or Qwen3.5-122B-A10B?
Neither: both take 262K tokens.
How many benchmarks is the Mistral Medium 3.5 vs Qwen3.5-122B-A10B comparison based on?
49 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3.5's coding index rests on 1 independent benchmark and Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.