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Phi 4 vs Mistral Small 3.1 24B

Updated October 21, 2026. 27 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Phi 4Microsoft
Coding
No data
Overall
5.9
Output $/M
$0.14
0
Mistral Small 3.1 24BMistral AI
Coding
No data
Overall
No data
Output $/M
$0.555
27
vs boards won of 27 shared

Decision reading

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

Phi 4 has the edge where output tokens cost 4.0x less, and where what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
27
Phi 4 only
18
Mistral Small 3.1 24B only
11
Like-for-like categories
5 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
Phi 4 not benchmarked, Mistral Small 3.1 24B not benchmarked.
Widest category
Coding, 12.6 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: entertainment and media: Phi 4 1162 against Mistral Small 3.1 24B 1250, 14.7 points apart on a 0 to 100 scale.
Output price
Phi 4 $0.14 against Mistral Small 3.1 24B $0.555 per million output tokens, 4.0x apart.
Context window
Phi 4 takes 16K tokens, Mistral Small 3.1 24B 128K.

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
CategoryPhi 4BarsMistral Small 3.1 24BTies
Coding02
Reasoning03
Math02
Knowledge04
General016
All shared boards027
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
LiveCodeBench (Artificial Analysis run)23.1%Not measuredOnly Phi 4 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%Not measuredOnly Phi 4 measured
LMArena Text: coding12311309Mistral Small 3.1 24B
LMArena Text: software and IT12281301Mistral Small 3.1 24B
Neither model has a result on the other 34 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
AA Intelligence Index5.9Not measuredOnly Phi 4 measured
Epoch Capabilities Index130.5Not measuredOnly Phi 4 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
τ²-Bench Telecom0.0%Not measuredOnly Phi 4 measured
BALROG11.6%Not measuredOnly Phi 4 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
GPQA Diamond (Artificial Analysis run)57.5%Not measuredOnly Phi 4 measured
Humanity's Last Exam (Artificial Analysis run)3.8%Not measuredOnly Phi 4 measured
GPQA Diamond (Epoch AI run)56.1%Not measuredOnly Phi 4 measured
LMArena Text: hard prompts12201278Mistral Small 3.1 24B
LMArena Text: expert12031257Mistral Small 3.1 24B
LMArena Text: hard prompts in English12301290Mistral Small 3.1 24B
LMArena Vision: diagramsNot measured1119Only Mistral Small 3.1 24B measured
LMArena Vision: homeworkNot measured1158Only Mistral Small 3.1 24B measured
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 Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
AA Math Index18.0Not measuredOnly Phi 4 measured
AIME 2025 (Artificial Analysis run)18.0%Not measuredOnly Phi 4 measured
OTIS Mock AIME13.8%Not measuredOnly Phi 4 measured
MATH level 564.9%Not measuredOnly Phi 4 measured
LMArena Text: math12461261Mistral Small 3.1 24B
LMArena Text: mathematical work12541271Mistral Small 3.1 24B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
MMLU Pro (Artificial Analysis run)71.4%Not measuredOnly Phi 4 measured
MMLU84.8%Not measuredOnly Phi 4 measured
LMArena Text: science12061265Mistral Small 3.1 24B
LMArena Text: medicine and healthcare12021267Mistral Small 3.1 24B
LMArena Text: legal and government12411271Mistral Small 3.1 24B
LMArena Text: business and finance11991257Mistral Small 3.1 24B
Neither model has a result on the other 11 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index016
General benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
IFBench23.5%Not measuredOnly Phi 4 measured
Long context reasoning (AA-LCR)0.0%Not measuredOnly Phi 4 measured
Creative writing (Lech Mazur)62.6%Not measuredOnly Phi 4 measured
LMArena Text12171277Mistral Small 3.1 24B
LMArena Text: instruction following12011263Mistral Small 3.1 24B
LMArena Text: creative writing11811252Mistral Small 3.1 24B
LMArena VisionNot measured1136Only Mistral Small 3.1 24B measured
LMArena Text: English12311295Mistral Small 3.1 24B
LMArena Text: non-English11971255Mistral Small 3.1 24B
LMArena Text: Chinese12121253Mistral Small 3.1 24B
LMArena Text: German12221266Mistral Small 3.1 24B
LMArena Text: Japanese11581208Mistral Small 3.1 24B
LMArena Text: Korean11511207Mistral Small 3.1 24B
LMArena Text: French12241273Mistral Small 3.1 24B
LMArena Text: Spanish12341284Mistral Small 3.1 24B
LMArena Text: Russian12091263Mistral Small 3.1 24B
LMArena Text: PolishNot measured1242Only Mistral Small 3.1 24B measured
LMArena Text: multi-turn12061270Mistral Small 3.1 24B
LMArena Text: longer queries12171299Mistral Small 3.1 24B
LMArena Text: writing and language11981268Mistral Small 3.1 24B
LMArena Text: entertainment and media11621250Mistral Small 3.1 24B
LMArena Vision: EnglishNot measured1157Only Mistral Small 3.1 24B measured
LMArena Vision: ChineseNot measured1155Only Mistral Small 3.1 24B measured
LMArena Vision: reading textNot measured1132Only Mistral Small 3.1 24B measured
LMArena Vision: humorNot measured1142Only Mistral Small 3.1 24B measured
LMArena Vision: captioningNot measured1153Only Mistral Small 3.1 24B measured
LMArena Vision: recognizing thingsNot measured1155Only Mistral Small 3.1 24B measured
LMArena Vision: creative writingNot measured1123Only Mistral Small 3.1 24B measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Phi 4 and Mistral Small 3.1 24B
BenchmarkPhi 4Mistral Small 3.1 24BLeader
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

Phi 4$0.0001Fits in one request
Mistral Small 3.1 24B$0.0006Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Phi 4$0.0039Exceeds the context window
Mistral Small 3.1 24B$0.019Fits in one request

Phi 4 costs less

Agent loop

200K input + 10K output tokens

Phi 4$0.015Exceeds the context window
Mistral Small 3.1 24B$0.076Exceeds the context window

Phi 4 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 Phi 4 and Mistral Small 3.1 24B
SpecificationMicrosoft Phi 4Mistral Small 3.1 24B
MakerMicrosoftMistral AI
WeightsOpen weightsOpen weights
ReleasedJanuary 10, 2025March 17, 2025
Context window16K128K
Input $/Mtok$0.07$0.351
Output $/Mtok$0.14$0.555
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Phi 4 better than Mistral Small 3.1 24B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Phi 4 has the edge where output tokens cost 4.0x less, and where what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Phi 4 or Mistral Small 3.1 24B?

Phi 4 costs $0.07 per million input tokens and $0.14 per million output tokens; Mistral Small 3.1 24B costs $0.351 and $0.555. Cost per solved task is known for neither of them.

Which has the bigger context window, Phi 4 or Mistral Small 3.1 24B?

Mistral Small 3.1 24B, with 128K tokens against 16K.

How many benchmarks is the Phi 4 vs Mistral Small 3.1 24B comparison based on?

27 benchmarks have a result for both models as of October 21, 2026. Phi 4's coding index rests on 0 independent benchmarks and Mistral Small 3.1 24B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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