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Llama 3.2 3B Instruct vs Mistral Medium 3

Updated October 21, 2026. 33 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Llama 3.2 3B Instruct Replace Mistral Medium 3
Llama 3.2 3B InstructMeta Llama
Coding
No data
Overall
5.7
Output $/M
$0.3325
1
Mistral Medium 3Mistral AI
Coding
No data
Overall
9.0
Output $/M
$2.00
32
vs boards won of 33 shared

Decision reading

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

Llama 3.2 3B Instruct has the edge where output tokens cost 6.0x less, and where what matters is LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model ALlama 3.2 3B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Medium 3Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
33
Llama 3.2 3B Instruct only
1
Mistral Medium 3 only
24
Like-for-like categories
7 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
Llama 3.2 3B Instruct not benchmarked, Mistral Medium 3 not benchmarked.
Widest category
Knowledge, 44.9 points apart on average over 5 shared benchmarks.
Widest single gap
LMArena Text: Russian: Llama 3.2 3B Instruct 949 against Mistral Medium 3 1359, 59.9 points apart on a 0 to 100 scale.
Output price
Llama 3.2 3B Instruct $0.3325 against Mistral Medium 3 $2.00 per million output tokens, 6.0x apart.
Context window
Both take 131K tokens.

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
CategoryLlama 3.2 3B InstructBarsMistral Medium 3Ties
Coding03
Intelligence01
Agentic work01
Reasoning14
Math04
Knowledge05
General014
All shared boards132
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
LiveCodeBench (Artificial Analysis run)8.3%40.0%Mistral Medium 3
Terminal-Bench Hard (Artificial Analysis run)Not measured3.8%Only Mistral Medium 3 measured
LMArena Text: coding10981385Mistral Medium 3
LMArena Text: software and IT11031385Mistral Medium 3
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 Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
AA Intelligence Index5.79.0Mistral Medium 3
Epoch Capabilities IndexNot measured134.0Only Mistral Medium 3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
τ²-Bench Telecom21.1%24.3%Mistral Medium 3
BALROG10.1%Not measuredOnly Llama 3.2 3B Instruct measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
Reasoning benchmarks for Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
GPQA Diamond (Artificial Analysis run)25.5%57.8%Mistral Medium 3
Humanity's Last Exam (Artificial Analysis run)5.3%4.1%Llama 3.2 3B Instruct
LMArena Text: hard prompts10951364Mistral Medium 3
LMArena Text: expert10901342Mistral Medium 3
LMArena Text: hard prompts in English11411374Mistral Medium 3
LMArena Vision: diagramsNot measured1155Only Mistral Medium 3 measured
LMArena Vision: homeworkNot measured1165Only Mistral Medium 3 measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
AA Math Index3.330.3Mistral Medium 3
AIME 2025 (Artificial Analysis run)3.3%30.3%Mistral Medium 3
LMArena Text: math11261353Mistral Medium 3
LMArena Text: mathematical work11281354Mistral Medium 3
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
MMLU Pro (Artificial Analysis run)34.7%76.0%Mistral Medium 3
LMArena Text: science11061381Mistral Medium 3
LMArena Text: medicine and healthcare11041381Mistral Medium 3
LMArena Text: legal and government11151384Mistral Medium 3
LMArena Text: business and finance10741352Mistral Medium 3
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
Design Arena: websitesNot measured1079Only Mistral Medium 3 measured
Design Arena: UI componentsNot measured1024Only Mistral Medium 3 measured
Design Arena: game devNot measured1018Only Mistral Medium 3 measured
Design Arena: data vizNot measured1034Only Mistral Medium 3 measured
Design Arena: 3DNot measured1083Only Mistral Medium 3 measured
Design Arena: all code categoriesNot measured1069Only 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 index014
General benchmarks for Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
IFBench26.2%39.3%Mistral Medium 3
Long context reasoning (AA-LCR)4.3%31.3%Mistral Medium 3
DTBenchNot measured62.3%Only Mistral Medium 3 measured
LMArena Text11101370Mistral Medium 3
LMArena Text: instruction following10891338Mistral Medium 3
LMArena Text: creative writing10941343Mistral Medium 3
LMArena VisionNot measured1157Only Mistral Medium 3 measured
LMArena Text: English11801385Mistral Medium 3
LMArena Text: non-English10191353Mistral Medium 3
LMArena Text: Chinese10171374Mistral Medium 3
LMArena Text: German10561377Mistral Medium 3
LMArena Text: JapaneseNot measured1316Only Mistral Medium 3 measured
LMArena Text: KoreanNot measured1304Only Mistral Medium 3 measured
LMArena Text: FrenchNot measured1368Only Mistral Medium 3 measured
LMArena Text: SpanishNot measured1364Only Mistral Medium 3 measured
LMArena Text: Russian9491359Mistral Medium 3
LMArena Text: PolishNot measured1371Only Mistral Medium 3 measured
LMArena Text: multi-turn11051384Mistral Medium 3
LMArena Text: longer queries11001360Mistral Medium 3
LMArena Text: writing and language10961352Mistral Medium 3
LMArena Text: entertainment and media10831335Mistral Medium 3
LMArena Vision: EnglishNot measured1172Only Mistral Medium 3 measured
LMArena Vision: ChineseNot measured1161Only Mistral Medium 3 measured
LMArena Vision: reading textNot measured1154Only Mistral Medium 3 measured
LMArena Vision: humorNot measured1145Only Mistral Medium 3 measured
LMArena Vision: captioningNot measured1094Only Mistral Medium 3 measured
LMArena Vision: recognizing thingsNot measured1141Only Mistral Medium 3 measured
LMArena Vision: creative writingNot measured1146Only Mistral Medium 3 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 Llama 3.2 3B Instruct and Mistral Medium 3
BenchmarkLlama 3.2 3B InstructMistral Medium 3Leader
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

Llama 3.2 3B Instruct$0.0002Fits in one request
Mistral Medium 3$0.0014Fits in one request

Llama 3.2 3B Instruct costs less

Repository review

50K input + 3K output tokens

Llama 3.2 3B Instruct$0.0035Fits in one request
Mistral Medium 3$0.026Fits in one request

Llama 3.2 3B Instruct costs less

Agent loop

200K input + 10K output tokens

Llama 3.2 3B Instruct$0.013Exceeds the context window
Mistral Medium 3$0.100Exceeds the context window

Llama 3.2 3B Instruct 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 Llama 3.2 3B Instruct and Mistral Medium 3
SpecificationMeta Llama 3.2 3B InstructMistral Medium 3
MakerMeta LlamaMistral AI
WeightsOpen weightsNo public weights listed
ReleasedSeptember 25, 2024May 7, 2025
Context window131K131K
Input $/Mtok$0.0505$0.40
Output $/Mtok$0.3325$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.2 3B Instruct better than Mistral Medium 3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Llama 3.2 3B Instruct has the edge where output tokens cost 6.0x less, and where what matters is LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, Llama 3.2 3B Instruct or Mistral Medium 3?

Llama 3.2 3B Instruct costs $0.0505 per million input tokens and $0.3325 per million output tokens; Mistral Medium 3 costs $0.40 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.2 3B Instruct or Mistral Medium 3?

Neither: both take 131K tokens.

How many benchmarks is the Llama 3.2 3B Instruct vs Mistral Medium 3 comparison based on?

33 benchmarks have a result for both models as of October 21, 2026. Llama 3.2 3B Instruct's coding index rests on 0 independent benchmarks and Mistral Medium 3's on 0. Where only one model has a result, the page says so instead of naming a winner.

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