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Mistral Medium 3.1 vs Qwen3.7 Plus

Qwen3.7 Plus leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 25.2 to 9.2, and Qwen3.7 Plus costs 1.6x less per output token ($1.28 vs $2.00 per million). Updated October 22, 2026; 57 benchmarks have a result for both.

Replace Mistral Medium 3.1 Replace Qwen3.7 Plus
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
0
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
57
vs boards won of 57 shared

Mistral Medium 3.1 or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
57
Mistral Medium 3.1 only
17
Qwen3.7 Plus only
18
Like-for-like categories
8 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, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Agentic work, 34.0 points apart on average over 2 shared benchmarks.
Widest single gap
τ²-Bench Telecom: Mistral Medium 3.1 40.6% against Qwen3.7 Plus 93.0%, 52.3 points apart on a 0 to 100 scale.
Output price
Mistral Medium 3.1 $2.00 against Qwen3.7 Plus $1.28 per million output tokens, 1.6x apart.
Context window
Mistral Medium 3.1 takes 131K tokens, Qwen3.7 Plus 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.

Boards won, where both have a result
CategoryMistral Medium 3.1BarsQwen3.7 PlusTies
Coding05
Intelligence01
Agentic work02
Reasoning07
Math02
Knowledge05
Web design08
General027
All shared boards057
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
AA Coding Index20.555.9Qwen3.7 Plus
LiveCodeBench (Vals AI)44.8%Not measuredOnly Mistral Medium 3.1 measured
Vibe Code Bench (Vals AI)Not measured46.4%Only Qwen3.7 Plus measured
Code migration (Vals AI)Not measured12.9%Only Qwen3.7 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
LiveCodeBench (Artificial Analysis run)40.6%Not measuredOnly Mistral Medium 3.1 measured
SciCode32.4%46.1%Qwen3.7 Plus
Terminal-Bench Hard (Artificial Analysis run)10.6%47.0%Qwen3.7 Plus
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
ALE-Bench210.2Not measuredOnly Mistral Medium 3.1 measured
LMArena Text: coding14331473Qwen3.7 Plus
LMArena Text: software and IT14361473Qwen3.7 Plus
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
AA Intelligence Index9.225.2Qwen3.7 Plus
Epoch Capabilities IndexNot measured147.0Only Qwen3.7 Plus measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
AA Agentic Index1.917.5Qwen3.7 Plus
Finance Agent (Vals AI)Not measured38.2%Only Qwen3.7 Plus measured
Tax Agent Bench (Vals AI)Not measured10.5%Only Qwen3.7 Plus measured
Legal Research Bench (Vals AI)Not measured16.4%Only Qwen3.7 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured49.3%Only Qwen3.7 Plus measured
τ²-Bench Telecom40.6%93.0%Qwen3.7 Plus
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
MMMU Pro (Vals AI)63.0%Not measuredOnly Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)58.8%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)4.7%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)Not measured87.9%Only Qwen3.7 Plus measured
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts14261460Qwen3.7 Plus
LMArena Text: expert14081466Qwen3.7 Plus
LMArena Text: hard prompts in English14351460Qwen3.7 Plus
LMArena Vision: diagrams11751292Qwen3.7 Plus
LMArena Vision: homework11651295Qwen3.7 Plus
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
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 measured93.3%Only Qwen3.7 Plus measured
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
LMArena Text: math14081467Qwen3.7 Plus
LMArena Text: mathematical work14121470Qwen3.7 Plus
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
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%66.2%Qwen3.7 Plus
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: science14441464Qwen3.7 Plus
LMArena Text: medicine and healthcare14491464Qwen3.7 Plus
LMArena Text: legal and government14391451Qwen3.7 Plus
LMArena Text: business and finance14181435Qwen3.7 Plus
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
Design Arena: websites11321269Qwen3.7 Plus
Design Arena: UI components10971258Qwen3.7 Plus
Design Arena: game dev10731261Qwen3.7 Plus
Design Arena: data viz11441276Qwen3.7 Plus
Design Arena: 3D10811238Qwen3.7 Plus
Design Arena: all code categories11201269Qwen3.7 Plus
Design Arena: SVG9921208Qwen3.7 Plus
Design Arena: ASCII art9971143Qwen3.7 Plus
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index027
General benchmarks for Mistral Medium 3.1 and Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench39.8%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)42.7%73.0%Qwen3.7 Plus
DTBench67.5%84.0%Qwen3.7 Plus
LMCA19.1%37.6%Qwen3.7 Plus
LMArena Text14241454Qwen3.7 Plus
LMArena Text: instruction following13981439Qwen3.7 Plus
LMArena Text: creative writing13911438Qwen3.7 Plus
LMArena Vision11721278Qwen3.7 Plus
LMArena Text: English14381458Qwen3.7 Plus
LMArena Text: non-English14081445Qwen3.7 Plus
LMArena Text: Chinese14471509Qwen3.7 Plus
LMArena Text: German14321471Qwen3.7 Plus
LMArena Text: Japanese13791412Qwen3.7 Plus
LMArena Text: Korean13801413Qwen3.7 Plus
LMArena Text: French14601472Qwen3.7 Plus
LMArena Text: Spanish14331457Qwen3.7 Plus
LMArena Text: Russian14111457Qwen3.7 Plus
LMArena Text: Polish14301449Qwen3.7 Plus
LMArena Text: multi-turn14181459Qwen3.7 Plus
LMArena Text: longer queries14061454Qwen3.7 Plus
LMArena Text: writing and language13951437Qwen3.7 Plus
LMArena Text: entertainment and media13901422Qwen3.7 Plus
LMArena Vision: English11791280Qwen3.7 Plus
LMArena Vision: Chinese11901332Qwen3.7 Plus
LMArena Vision: reading text11751288Qwen3.7 Plus
LMArena Vision: humor11681261Qwen3.7 Plus
LMArena Vision: captioning1145Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: recognizing things1147Not measuredOnly Mistral Medium 3.1 measured
LMArena Vision: creative writing12001258Qwen3.7 Plus
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 14 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 Qwen3.7 Plus
BenchmarkMistral Medium 3.1Qwen3.7 PlusLeader
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
Qwen3.7 Plus$0.0010Fits in one request

Qwen3.7 Plus costs less

Repository review

50K input + 3K output tokens

Mistral Medium 3.1$0.026Fits in one request
Qwen3.7 Plus$0.020Fits in one request

Qwen3.7 Plus costs less

Agent loop

200K input + 10K output tokens

Mistral Medium 3.1$0.100Exceeds the context window
Qwen3.7 Plus$0.077Fits in one request

Qwen3.7 Plus 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 Qwen3.7 Plus
SpecificationMistral Medium 3.1Qwen3.7 Plus
MakerMistral AIQwen
WeightsNo public weights listedNo public weights listed
ReleasedAugust 13, 2025June 3, 2026
Context window131K1M
Input $/Mtok$0.40$0.32
Output $/Mtok$2.00$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it02
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Medium 3.1 better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, Mistral Medium 3.1 or Qwen3.7 Plus?

Mistral Medium 3.1 costs $0.40 per million input tokens and $2.00 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.

Which has the bigger context window, Mistral Medium 3.1 or Qwen3.7 Plus?

Qwen3.7 Plus, with 1M tokens against 131K.

How many benchmarks is the Mistral Medium 3.1 vs Qwen3.7 Plus comparison based on?

57 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 Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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