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Mistral Small 3 vs Qwen3.5-27B

Qwen3.5-27B leads Mistral Small 3 on the Artificial Analysis Intelligence Index, 22.9 to 6.7, and Mistral Small 3 costs 19.5x less per output token ($0.08 vs $1.56 per million). Updated October 22, 2026; 32 benchmarks have a result for both.

Replace Mistral Small 3 Replace Qwen3.5-27B
Mistral Small 3Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.08
0
Qwen3.5-27BQwen
Coding
No data
Overall
No data
Output $/M
$1.56
32
vs boards won of 32 shared

Mistral Small 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 Small 3 for output tokens 19.5x cheaper ($0.08 vs $1.56 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AMistral Small 3Mistral AINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-27BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
32
Mistral Small 3 only
4
Qwen3.5-27B only
21
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 Small 3 not benchmarked, Qwen3.5-27B not benchmarked.
Widest category
Agentic work, 74.3 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): Mistral Small 3 0.0% against Qwen3.5-27B 77.7%, 77.7 points apart on a 0 to 100 scale.
Output price
Mistral Small 3 $0.08 against Qwen3.5-27B $1.56 per million output tokens, 19.5x apart.
Context window
Mistral Small 3 takes 33K 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 Small 3BarsQwen3.5-27BTies
Coding02
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge04
General017
All shared boards032
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Mistral Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
LMArena WebDevNot measured1358Only Qwen3.5-27B measured
LiveCodeBench (Artificial Analysis run)25.2%Not measuredOnly Mistral Small 3 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured32.6%Only Qwen3.5-27B measured
WeirdMLNot measured39.5%Only Qwen3.5-27B measured
ALE-BenchNot measured349.4Only Qwen3.5-27B measured
LMArena Text: coding12461427Qwen3.5-27B
LMArena Text: software and IT12481431Qwen3.5-27B
LMArena WebDev: ReactNot measured1346Only Qwen3.5-27B measured
LMArena WebDev: HTMLNot measured1386Only Qwen3.5-27B measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mistral Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
AA Intelligence Index6.722.9Qwen3.5-27B
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 Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
τ²-Bench Telecom19.6%93.9%Qwen3.5-27B
Vending-Bench 2Not measured$202Only Qwen3.5-27B measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Mistral Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
GPQA Diamond (Artificial Analysis run)46.2%85.8%Qwen3.5-27B
Humanity's Last Exam (Artificial Analysis run)3.8%23.9%Qwen3.5-27B
LMArena Text: hard prompts12331415Qwen3.5-27B
LMArena Text: expert12021427Qwen3.5-27B
LMArena Text: hard prompts in English12431429Qwen3.5-27B
LMArena Vision: diagramsNot measured1249Only Qwen3.5-27B measured
LMArena Vision: homeworkNot measured1256Only Qwen3.5-27B measured
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Mistral Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
AA Math Index4.3Not measuredOnly Mistral Small 3 measured
AIME 2025 (Artificial Analysis run)4.3%Not measuredOnly Mistral Small 3 measured
LMArena Text: math12401429Qwen3.5-27B
LMArena Text: mathematical work12431429Qwen3.5-27B
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 Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
MMLU Pro (Artificial Analysis run)65.2%Not measuredOnly Mistral Small 3 measured
LMArena Text: science12351437Qwen3.5-27B
LMArena Text: medicine and healthcare12151425Qwen3.5-27B
LMArena Text: legal and government12191405Qwen3.5-27B
LMArena Text: business and finance12051399Qwen3.5-27B
Neither model has a result on the other 13 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Mistral Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
General benchmarks for Mistral Small 3 and Qwen3.5-27B
BenchmarkMistral Small 3Qwen3.5-27BLeader
IFBench26.4%75.6%Qwen3.5-27B
Long context reasoning (AA-LCR)0.0%77.7%Qwen3.5-27B
DTBenchNot measured82.4%Only Qwen3.5-27B measured
LMCANot measured34.0%Only Qwen3.5-27B measured
LMArena Text12341409Qwen3.5-27B
LMArena Text: instruction following12141393Qwen3.5-27B
LMArena Text: creative writing11941362Qwen3.5-27B
LMArena VisionNot measured1241Only Qwen3.5-27B measured
LMArena Text: English12561425Qwen3.5-27B
LMArena Text: non-English11981390Qwen3.5-27B
LMArena Text: Chinese12041478Qwen3.5-27B
LMArena Text: German12111392Qwen3.5-27B
LMArena Text: Japanese11111346Qwen3.5-27B
LMArena Text: Korean11881359Qwen3.5-27B
LMArena Text: French12041410Qwen3.5-27B
LMArena Text: SpanishNot measured1407Only Qwen3.5-27B measured
LMArena Text: Russian12161390Qwen3.5-27B
LMArena Text: PolishNot measured1375Only Qwen3.5-27B measured
LMArena Text: multi-turn12171410Qwen3.5-27B
LMArena Text: longer queries12461413Qwen3.5-27B
LMArena Text: writing and language12141380Qwen3.5-27B
LMArena Text: entertainment and media11841363Qwen3.5-27B
LMArena Vision: EnglishNot measured1246Only Qwen3.5-27B measured
LMArena Vision: ChineseNot measured1301Only Qwen3.5-27B measured
LMArena Vision: reading textNot measured1246Only Qwen3.5-27B measured
LMArena Vision: humorNot measured1227Only Qwen3.5-27B measured
LMArena Vision: captioningNot measured1170Only Qwen3.5-27B measured
LMArena Vision: recognizing thingsNot measured1210Only Qwen3.5-27B measured
LMArena Vision: creative writingNot measured1224Only Qwen3.5-27B 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 Small 3 and Qwen3.5-27B
BenchmarkMistral Small 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 Small 3$0.0001Fits in one request
Qwen3.5-27B$0.0010Fits in one request

Mistral Small 3 costs less

Repository review

50K input + 3K output tokens

Mistral Small 3$0.0027Exceeds the context window
Qwen3.5-27B$0.014Fits in one request

Mistral Small 3 costs less

Agent loop

200K input + 10K output tokens

Mistral Small 3$0.011Exceeds the context window
Qwen3.5-27B$0.055Fits in one request

Mistral Small 3 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 Small 3 and Qwen3.5-27B
SpecificationMistral Small 3Qwen3.5-27B
MakerMistral AIQwen
WeightsOpen weightsOpen weights
ReleasedJanuary 30, 2025February 25, 2026
Context window33K262K
Input $/Mtok$0.05$0.195
Output $/Mtok$0.08$1.56
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Small 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 Small 3 for output tokens 19.5x cheaper ($0.08 vs $1.56 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

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

Mistral Small 3 costs $0.05 per million input tokens and $0.08 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 Small 3 or Qwen3.5-27B?

Qwen3.5-27B, with 262K tokens against 33K.

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

32 benchmarks have a result for both models as of October 22, 2026. Mistral Small 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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