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Mistral Medium 3 vs Qwen3.5-27B

Qwen3.5-27B leads Mistral Medium 3 on the Artificial Analysis Intelligence Index, 22.9 to 9.0, and Qwen3.5-27B costs 1.3x less per output token ($1.56 vs $2.00 per million). Updated October 22, 2026; 46 benchmarks have a result for both.

Replace Mistral Medium 3 Replace Qwen3.5-27B
Mistral Medium 3Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
0
Qwen3.5-27BQwen
Coding
No data
Overall
No data
Output $/M
$1.56
46
vs boards won of 46 shared

Mistral Medium 3 or Qwen3.5-27B: which to pick

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

Pick Mistral Medium 3 for work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model AMistral Medium 3Mistral AINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-27BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
46
Mistral Medium 3 only
11
Qwen3.5-27B only
8
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 not benchmarked, Qwen3.5-27B not benchmarked.
Widest category
Agentic work, 69.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Mistral Medium 3 24.3% against Qwen3.5-27B 93.9%, 69.6 points apart on a 0 to 100 scale.
Output price
Mistral Medium 3 $2.00 against Qwen3.5-27B $1.56 per million output tokens, 1.3x apart.
Context window
Mistral Medium 3 takes 131K tokens, Qwen3.5-27B 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 3BarsQwen3.5-27BTies
Coding03
Intelligence01
Agentic work01
Reasoning07
Math02
Knowledge04
General028
All shared boards046
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
LMArena WebDevNot measured1358Only Qwen3.5-27B measured
LiveCodeBench (Artificial Analysis run)40.0%Not measuredOnly Mistral Medium 3 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%32.6%Qwen3.5-27B
WeirdMLNot measured39.5%Only Qwen3.5-27B measured
ALE-BenchNot measured349.4Only Qwen3.5-27B measured
LMArena Text: coding13851427Qwen3.5-27B
LMArena Text: software and IT13851431Qwen3.5-27B
LMArena WebDev: ReactNot measured1346Only Qwen3.5-27B measured
LMArena WebDev: HTMLNot measured1386Only Qwen3.5-27B measured
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
AA Intelligence Index9.022.9Qwen3.5-27B
Epoch Capabilities Index134.0Not measuredOnly Mistral Medium 3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
τ²-Bench Telecom24.3%93.9%Qwen3.5-27B
Vending-Bench 2Not measured$202Only Qwen3.5-27B measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
GPQA Diamond (Artificial Analysis run)57.8%85.8%Qwen3.5-27B
Humanity's Last Exam (Artificial Analysis run)4.1%23.9%Qwen3.5-27B
LMArena Text: hard prompts13641415Qwen3.5-27B
LMArena Text: expert13421427Qwen3.5-27B
LMArena Text: hard prompts in English13741429Qwen3.5-27B
LMArena Vision: diagrams11551249Qwen3.5-27B
LMArena Vision: homework11651256Qwen3.5-27B
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
AA Math Index30.3Not measuredOnly Mistral Medium 3 measured
AIME 2025 (Artificial Analysis run)30.3%Not measuredOnly Mistral Medium 3 measured
LMArena Text: math13531429Qwen3.5-27B
LMArena Text: mathematical work13541429Qwen3.5-27B
MathArenaNot measured15.8%Only Qwen3.5-27B measured
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
MMLU Pro (Artificial Analysis run)76.0%Not measuredOnly Mistral Medium 3 measured
LMArena Text: science13811437Qwen3.5-27B
LMArena Text: medicine and healthcare13811425Qwen3.5-27B
LMArena Text: legal and government13841405Qwen3.5-27B
LMArena Text: business and finance13521399Qwen3.5-27B
Neither model has a result on the other 15 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
Design Arena: websites1079Not measuredOnly Mistral Medium 3 measured
Design Arena: UI components1022Not measuredOnly Mistral Medium 3 measured
Design Arena: game dev1017Not measuredOnly Mistral Medium 3 measured
Design Arena: data viz1034Not measuredOnly Mistral Medium 3 measured
Design Arena: 3D1083Not measuredOnly Mistral Medium 3 measured
Design Arena: all code categories1068Not measuredOnly Mistral Medium 3 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index028
General benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
IFBench39.3%75.6%Qwen3.5-27B
Long context reasoning (AA-LCR)31.3%77.7%Qwen3.5-27B
DTBench62.3%82.4%Qwen3.5-27B
LMCANot measured34.0%Only Qwen3.5-27B measured
LMArena Text13701409Qwen3.5-27B
LMArena Text: instruction following13381393Qwen3.5-27B
LMArena Text: creative writing13431362Qwen3.5-27B
LMArena Vision11571241Qwen3.5-27B
LMArena Text: English13851425Qwen3.5-27B
LMArena Text: non-English13531390Qwen3.5-27B
LMArena Text: Chinese13741478Qwen3.5-27B
LMArena Text: German13771392Qwen3.5-27B
LMArena Text: Japanese13161346Qwen3.5-27B
LMArena Text: Korean13041359Qwen3.5-27B
LMArena Text: French13681410Qwen3.5-27B
LMArena Text: Spanish13641407Qwen3.5-27B
LMArena Text: Russian13591390Qwen3.5-27B
LMArena Text: Polish13711375Qwen3.5-27B
LMArena Text: multi-turn13841410Qwen3.5-27B
LMArena Text: longer queries13601413Qwen3.5-27B
LMArena Text: writing and language13521380Qwen3.5-27B
LMArena Text: entertainment and media13351363Qwen3.5-27B
LMArena Vision: English11721246Qwen3.5-27B
LMArena Vision: Chinese11611301Qwen3.5-27B
LMArena Vision: reading text11541246Qwen3.5-27B
LMArena Vision: humor11451227Qwen3.5-27B
LMArena Vision: captioning10941170Qwen3.5-27B
LMArena Vision: recognizing things11411210Qwen3.5-27B
LMArena Vision: creative writing11461224Qwen3.5-27B
Neither model has a result on the other 19 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mistral Medium 3 and Qwen3.5-27B
BenchmarkMistral Medium 3Qwen3.5-27BLeader
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$0.0014Fits in one request
Qwen3.5-27B$0.0010Fits in one request

Qwen3.5-27B costs less

Repository review

50K input + 3K output tokens

Mistral Medium 3$0.026Fits in one request
Qwen3.5-27B$0.014Fits in one request

Qwen3.5-27B costs less

Agent loop

200K input + 10K output tokens

Mistral Medium 3$0.100Exceeds the context window
Qwen3.5-27B$0.055Fits in one request

Qwen3.5-27B 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 and Qwen3.5-27B
SpecificationMistral Medium 3Qwen3.5-27B
MakerMistral AIQwen
WeightsNo public weights listedOpen weights
ReleasedMay 7, 2025February 25, 2026
Context window131K262K
Input $/Mtok$0.40$0.195
Output $/Mtok$2.00$1.56
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Medium 3 better than Qwen3.5-27B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Medium 3 for work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, Mistral Medium 3 or Qwen3.5-27B?

Mistral Medium 3 costs $0.40 per million input tokens and $2.00 per million output tokens; Qwen3.5-27B costs $0.195 and $1.56. Cost per solved task is known for neither of them.

Which has the bigger context window, Mistral Medium 3 or Qwen3.5-27B?

Qwen3.5-27B, with 262K tokens against 131K.

How many benchmarks is the Mistral Medium 3 vs Qwen3.5-27B comparison based on?

46 benchmarks have a result for both models as of October 22, 2026. Mistral Medium 3's coding index rests on 0 independent benchmarks and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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