Enter opens the highlighted result. Esc closes.

Mistral Medium 3.1 vs Qwen3.5-122B-A10B

Qwen3.5-122B-A10B leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 17.7 to 9.2, at about the same output price ($2.08 vs $2.00 per million). Updated October 22, 2026; 47 benchmarks have a result for both.

Replace Mistral Medium 3.1 Replace Qwen3.5-122B-A10B
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
21
Qwen3.5-122B-A10BQwen
Coding
No data
Overall
No data
Output $/M
$2.08
26
vs boards won of 47 shared

Mistral Medium 3.1 or Qwen3.5-122B-A10B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Mistral Medium 3.1 for output tokens 1.0x cheaper ($2.00 vs $2.08 per million) and work measured by AA Coding Index or SciCode, where it leads.

Model AMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-122B-A10BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
47
Mistral Medium 3.1 only
27
Qwen3.5-122B-A10B only
4
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.

At a glance

Coding index
Mistral Medium 3.1 not benchmarked, Qwen3.5-122B-A10B not benchmarked.
Widest category
Agentic work, 52.9 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Mistral Medium 3.1 40.6% against Qwen3.5-122B-A10B 93.6%, 52.9 points apart on a 0 to 100 scale.
Output price
Mistral Medium 3.1 $2.00 against Qwen3.5-122B-A10B $2.08 per million output tokens, 1.0x apart.
Context window
Mistral Medium 3.1 takes 131K tokens, Qwen3.5-122B-A10B 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.

Boards won, where both have a result
CategoryMistral Medium 3.1BarsQwen3.5-122B-A10BTies
Coding14
Intelligence01
Agentic work01
Reasoning25
Math02
Knowledge40
General1413
All shared boards2126
CodingLike-for-likeSix of these boards feed the Vibe Coding Index14
Coding benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
LMArena WebDevNot measured1361Only Qwen3.5-122B-A10B measured
AA Coding Index20.543.3Qwen3.5-122B-A10B
LiveCodeBench (Vals AI)44.8%Not measuredOnly Mistral Medium 3.1 measured
LiveCodeBench (Artificial Analysis run)40.6%Not measuredOnly Mistral Medium 3.1 measured
SciCode32.4%39.7%Qwen3.5-122B-A10B
Terminal-Bench Hard (Artificial Analysis run)10.6%31.1%Qwen3.5-122B-A10B
ALE-Bench210.2Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: coding14331436Qwen3.5-122B-A10B
LMArena Text: software and IT14361436Mistral Medium 3.1
LMArena WebDev: ReactNot measured1353Only Qwen3.5-122B-A10B measured
LMArena WebDev: HTMLNot measured1351Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
AA Intelligence Index9.217.7Qwen3.5-122B-A10B
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
AA Agentic Index1.9Not measuredOnly Mistral Medium 3.1 measured
τ²-Bench Telecom40.6%93.6%Qwen3.5-122B-A10B
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index25
Reasoning benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
MMMU Pro (Vals AI)63.0%Not measuredOnly Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)58.8%85.7%Qwen3.5-122B-A10B
Humanity's Last Exam (Artificial Analysis run)4.7%25.2%Qwen3.5-122B-A10B
Mystery game puzzlesNot measured17.0%Only Qwen3.5-122B-A10B measured
LMArena Text: hard prompts14261421Mistral Medium 3.1
LMArena Text: expert14081431Qwen3.5-122B-A10B
LMArena Text: hard prompts in English14351431Mistral Medium 3.1
LMArena Vision: diagrams11751249Qwen3.5-122B-A10B
LMArena Vision: homework11651261Qwen3.5-122B-A10B
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
AIME42.3%Not measuredOnly Mistral Medium 3.1 measured
MATH 500 (Vals AI)87.0%Not measuredOnly Mistral Medium 3.1 measured
MGSM (Vals AI)90.9%Not measuredOnly Mistral Medium 3.1 measured
AA Math Index38.3Not measuredOnly Mistral Medium 3.1 measured
AIME 2025 (Artificial Analysis run)38.3%Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: math14081431Qwen3.5-122B-A10B
LMArena Text: mathematical work14121431Qwen3.5-122B-A10B
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
MMLU Pro75.3%Not measuredOnly Mistral Medium 3.1 measured
LegalBench (Vals AI)62.0%Not measuredOnly Mistral Medium 3.1 measured
CorpFin (Vals AI)50.7%Not measuredOnly Mistral Medium 3.1 measured
TaxEval (Vals AI)70.3%Not measuredOnly Mistral Medium 3.1 measured
MortgageTax (Vals AI)36.5%Not measuredOnly Mistral Medium 3.1 measured
MedQA (Vals AI)78.2%Not measuredOnly Mistral Medium 3.1 measured
MMLU Pro (Artificial Analysis run)68.3%Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: science14441432Mistral Medium 3.1
LMArena Text: medicine and healthcare14491423Mistral Medium 3.1
LMArena Text: legal and government14391422Mistral Medium 3.1
LMArena Text: business and finance14181414Mistral Medium 3.1
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
Web design benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
Design Arena: websites1132Not measuredOnly Mistral Medium 3.1 measured
Design Arena: UI components1097Not measuredOnly Mistral Medium 3.1 measured
Design Arena: game dev1073Not measuredOnly Mistral Medium 3.1 measured
Design Arena: data viz1144Not measuredOnly Mistral Medium 3.1 measured
Design Arena: 3D1081Not measuredOnly Mistral Medium 3.1 measured
Design Arena: all code categories1120Not measuredOnly Mistral Medium 3.1 measured
Design Arena: SVG992Not measuredOnly Mistral Medium 3.1 measured
Design Arena: ASCII art997Not measuredOnly Mistral Medium 3.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index1413
General benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
IFBench39.8%75.7%Qwen3.5-122B-A10B
Long context reasoning (AA-LCR)42.7%76.3%Qwen3.5-122B-A10B
DTBench67.5%84.3%Qwen3.5-122B-A10B
LMCA19.1%32.2%Qwen3.5-122B-A10B
LMArena Text14241417Mistral Medium 3.1
LMArena Text: instruction following13981399Qwen3.5-122B-A10B
LMArena Text: creative writing13911368Mistral Medium 3.1
LMArena Vision11721244Qwen3.5-122B-A10B
LMArena Text: English14381428Mistral Medium 3.1
LMArena Text: non-English14081401Mistral Medium 3.1
LMArena Text: Chinese14471463Qwen3.5-122B-A10B
LMArena Text: German14321425Mistral Medium 3.1
LMArena Text: Japanese13791367Mistral Medium 3.1
LMArena Text: Korean13801353Mistral Medium 3.1
LMArena Text: French14601443Mistral Medium 3.1
LMArena Text: Spanish14331425Mistral Medium 3.1
LMArena Text: Russian14111400Mistral Medium 3.1
LMArena Text: Polish14301398Mistral Medium 3.1
LMArena Text: multi-turn14181416Mistral Medium 3.1
LMArena Text: longer queries14061410Qwen3.5-122B-A10B
LMArena Text: writing and language13951387Mistral Medium 3.1
LMArena Text: entertainment and media13901366Mistral Medium 3.1
LMArena Vision: English11791249Qwen3.5-122B-A10B
LMArena Vision: Chinese11901301Qwen3.5-122B-A10B
LMArena Vision: reading text11751251Qwen3.5-122B-A10B
LMArena Vision: humor11681243Qwen3.5-122B-A10B
LMArena Vision: captioning1145Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: recognizing things1147Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: creative writing12001220Qwen3.5-122B-A10B
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mistral Medium 3.1 and Qwen3.5-122B-A10B
BenchmarkMistral Medium 3.1Qwen3.5-122B-A10BLeader
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

Mistral Medium 3.1$0.0014Fits in one request
Qwen3.5-122B-A10B$0.0013Fits in one request

Qwen3.5-122B-A10B costs less

Repository review

50K input + 3K output tokens

Mistral Medium 3.1$0.026Fits in one request
Qwen3.5-122B-A10B$0.019Fits in one request

Qwen3.5-122B-A10B costs less

Agent loop

200K input + 10K output tokens

Mistral Medium 3.1$0.100Exceeds the context window
Qwen3.5-122B-A10B$0.073Fits in one request

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.

Specifications of Mistral Medium 3.1 and Qwen3.5-122B-A10B
SpecificationMistral Medium 3.1Qwen3.5-122B-A10B
MakerMistral AIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 13, 2025February 25, 2026
Context window131K262K
Input $/Mtok$0.40$0.26
Output $/Mtok$2.00$2.08
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Medium 3.1 better than Qwen3.5-122B-A10B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Medium 3.1 for output tokens 1.0x cheaper ($2.00 vs $2.08 per million) and work measured by AA Coding Index or SciCode, where it leads.

Which is cheaper, Mistral Medium 3.1 or Qwen3.5-122B-A10B?

Mistral Medium 3.1 costs $0.40 per million input tokens and $2.00 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for neither of them.

Which has the bigger context window, Mistral Medium 3.1 or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B, with 262K tokens against 131K.

How many benchmarks is the Mistral Medium 3.1 vs Qwen3.5-122B-A10B comparison based on?

47 benchmarks have a result for both models as of October 22, 2026. Mistral Medium 3.1's coding index rests on 0 independent benchmarks and Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next