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Mistral Medium 3.1 vs Qwen3.5-9B

Qwen3.5-9B leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 13.3 to 9.2, and Qwen3.5-9B costs 13.3x less per output token ($0.15 vs $2.00 per million). Updated October 22, 2026; 11 benchmarks have a result for both.

Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
1
Qwen3.5-9BQwen
Coding
No data
Overall
No data
Output $/M
$0.15
10
vs boards won of 11 shared

Mistral Medium 3.1 or Qwen3.5-9B: which to pick

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

Pick Mistral Medium 3.1 for work measured by AA Coding Index or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Shared results
11
Mistral Medium 3.1 only
63
Qwen3.5-9B only
4
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.

At a glance

Coding index
Mistral Medium 3.1 not benchmarked, Qwen3.5-9B not benchmarked.
Widest category
Agentic work, 46.2 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Mistral Medium 3.1 40.6% against Qwen3.5-9B 86.8%, 46.2 points apart on a 0 to 100 scale.
Output price
Mistral Medium 3.1 $2.00 against Qwen3.5-9B $0.15 per million output tokens, 13.3x apart.
Context window
Mistral Medium 3.1 takes 131K tokens, Qwen3.5-9B 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 3.1BarsQwen3.5-9BTies
Coding12
Intelligence01
Agentic work01
Reasoning02
General04
All shared boards110
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
Coding benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
AA Coding Index20.523.5Qwen3.5-9B
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%29.5%Mistral Medium 3.1
Terminal-Bench Hard (Artificial Analysis run)10.6%24.2%Qwen3.5-9B
Terminal-BenchNot measured9.2%Only Qwen3.5-9B measured
ALE-Bench210.2Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: coding1433Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: software and IT1436Not measuredOnly Mistral Medium 3.1 measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
AA Intelligence Index9.213.3Qwen3.5-9B
Epoch Capabilities IndexNot measured139.3Only Qwen3.5-9B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
AA Agentic Index1.9Not measuredOnly Mistral Medium 3.1 measured
τ²-Bench Telecom40.6%86.8%Qwen3.5-9B
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
MMMU Pro (Vals AI)63.0%Not measuredOnly Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)58.8%80.6%Qwen3.5-9B
Humanity's Last Exam (Artificial Analysis run)4.7%14.9%Qwen3.5-9B
GPQA Diamond (Epoch AI run)Not measured79.0%Only Qwen3.5-9B measured
LMArena Text: hard prompts1426Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: expert1408Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: hard prompts in English1435Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: diagrams1175Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: homework1165Not measuredOnly Mistral Medium 3.1 measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Math benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
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
OTIS Mock AIMENot measured61.7%Only Qwen3.5-9B measured
LMArena Text: math1408Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: mathematical work1412Not measuredOnly Mistral Medium 3.1 measured
Neither model has a result on the other 5 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Knowledge benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
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: science1444Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: medicine and healthcare1449Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: legal and government1439Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: business and finance1418Not measuredOnly Mistral Medium 3.1 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
Web design benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
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 index04
General benchmarks for Mistral Medium 3.1 and Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
IFBench39.8%66.7%Qwen3.5-9B
Long context reasoning (AA-LCR)42.7%70.0%Qwen3.5-9B
DTBench67.5%71.2%Qwen3.5-9B
LMCA19.1%24.5%Qwen3.5-9B
LMArena Text1424Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: instruction following1398Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: creative writing1391Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision1172Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: English1438Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: non-English1408Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: Chinese1447Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: German1432Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: Japanese1379Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: Korean1380Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: French1460Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: Spanish1433Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: Russian1411Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: Polish1430Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: multi-turn1418Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: longer queries1406Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: writing and language1395Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: entertainment and media1390Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: English1179Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: Chinese1190Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: reading text1175Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: humor1168Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: captioning1145Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: recognizing things1147Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: creative writing1200Not measuredOnly Mistral Medium 3.1 measured
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 Qwen3.5-9B
BenchmarkMistral Medium 3.1Qwen3.5-9BLeader
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
Qwen3.5-9B$0.0002Fits in one request

Qwen3.5-9B costs less

Repository review

50K input + 3K output tokens

Mistral Medium 3.1$0.026Fits in one request
Qwen3.5-9B$0.0054Fits in one request

Qwen3.5-9B costs less

Agent loop

200K input + 10K output tokens

Mistral Medium 3.1$0.100Exceeds the context window
Qwen3.5-9B$0.021Fits in one request

Qwen3.5-9B 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 Qwen3.5-9B
SpecificationMistral Medium 3.1Qwen3.5-9B
MakerMistral AIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 13, 2025March 10, 2026
Context window131K262K
Input $/Mtok$0.40$0.10
Output $/Mtok$2.00$0.15
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Medium 3.1 better than Qwen3.5-9B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Medium 3.1 for work measured by AA Coding Index or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, Mistral Medium 3.1 or Qwen3.5-9B?

Mistral Medium 3.1 costs $0.40 per million input tokens and $2.00 per million output tokens; Qwen3.5-9B costs $0.10 and $0.15. Cost per solved task is known for neither of them.

Which has the bigger context window, Mistral Medium 3.1 or Qwen3.5-9B?

Qwen3.5-9B, with 262K tokens against 131K.

How many benchmarks is the Mistral Medium 3.1 vs Qwen3.5-9B comparison based on?

11 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 Qwen3.5-9B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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