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Llama 3.2 1B Instruct vs Mistral Small 3

Mistral Small 3 leads Llama 3.2 1B Instruct on the Artificial Analysis Intelligence Index, 6.7 to 4.8, and Mistral Small 3 costs 2.5x less per output token ($0.08 vs $0.201 per million). Updated October 21, 2026; 33 benchmarks have a result for both.

Replace Llama 3.2 1B Instruct Replace Mistral Small 3
Llama 3.2 1B InstructMeta Llama
Coding
No data
Overall
9.6
Output $/M
$0.201
2
Mistral Small 3Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.08
31
vs boards won of 33 shared

Llama 3.2 1B Instruct or Mistral Small 3: which to pick

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

Pick Llama 3.2 1B Instruct for a larger context window (60K against 33K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model ALlama 3.2 1B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Small 3Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
33
Llama 3.2 1B Instruct only
5
Mistral Small 3 only
3
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
Llama 3.2 1B Instruct not benchmarked, Mistral Small 3 not benchmarked.
Widest category
Knowledge, 33.7 points apart on average over 5 shared benchmarks.
Widest single gap
MMLU Pro (Artificial Analysis run): Llama 3.2 1B Instruct 20.0% against Mistral Small 3 65.2%, 45.2 points apart on a 0 to 100 scale.
Output price
Llama 3.2 1B Instruct $0.201 against Mistral Small 3 $0.08 per million output tokens, 2.5x apart.
Context window
Llama 3.2 1B Instruct takes 60K tokens, Mistral Small 3 33K.

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 1B InstructBarsMistral Small 3Ties
Coding03
Intelligence01
Agentic work01
Reasoning14
Math04
Knowledge05
General113
All shared boards231
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
LiveCodeBench (Artificial Analysis run)1.9%25.2%Mistral Small 3
Terminal-Bench Hard (Artificial Analysis run)0.0%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: coding10701246Mistral Small 3
LMArena Text: software and IT10561248Mistral Small 3
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
AA Intelligence Index4.86.7Mistral Small 3
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 Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
τ²-Bench Telecom0.0%19.6%Mistral Small 3
BALROG6.6%Not measuredOnly Llama 3.2 1B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)10.8%Not measuredOnly Llama 3.2 1B Instruct measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
Reasoning benchmarks for Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
GPQA Diamond (Artificial Analysis run)19.6%46.2%Mistral Small 3
Humanity's Last Exam (Artificial Analysis run)5.5%3.8%Llama 3.2 1B Instruct
GPQA Diamond (Epoch AI run)23.9%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: hard prompts10441233Mistral Small 3
LMArena Text: expert10071202Mistral Small 3
LMArena Text: hard prompts in English10871243Mistral Small 3
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
AA Math Index0.04.3Mistral Small 3
AIME 2025 (Artificial Analysis run)0.0%4.3%Mistral Small 3
OTIS Mock AIME0.6%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: math10861240Mistral Small 3
LMArena Text: mathematical work10981243Mistral Small 3
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
MMLU Pro (Artificial Analysis run)20.0%65.2%Mistral Small 3
LMArena Text: science10551235Mistral Small 3
LMArena Text: medicine and healthcare10091215Mistral Small 3
LMArena Text: legal and government10711219Mistral Small 3
LMArena Text: business and finance10001205Mistral Small 3
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 Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index113
General benchmarks for Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 3Leader
IFBench22.8%26.4%Mistral Small 3
Long context reasoning (AA-LCR)6.7%0.0%Llama 3.2 1B Instruct
LMArena Text10551234Mistral Small 3
LMArena Text: instruction following10311214Mistral Small 3
LMArena Text: creative writing10331194Mistral Small 3
LMArena Text: English11171256Mistral Small 3
LMArena Text: non-English9731198Mistral Small 3
LMArena Text: Chinese9591204Mistral Small 3
LMArena Text: German10141211Mistral Small 3
LMArena Text: JapaneseNot measured1111Only Mistral Small 3 measured
LMArena Text: KoreanNot measured1188Only Mistral Small 3 measured
LMArena Text: FrenchNot measured1204Only Mistral Small 3 measured
LMArena Text: Russian9411216Mistral Small 3
LMArena Text: multi-turn10301217Mistral Small 3
LMArena Text: longer queries10501246Mistral Small 3
LMArena Text: writing and language10301214Mistral Small 3
LMArena Text: entertainment and media10251184Mistral Small 3
Neither model has a result on the other 29 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Llama 3.2 1B Instruct and Mistral Small 3
BenchmarkLlama 3.2 1B InstructMistral Small 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 1B Instruct$0.0001Fits in one request
Mistral Small 3$0.0001Fits in one request

Mistral Small 3 costs less

Repository review

50K input + 3K output tokens

Llama 3.2 1B Instruct$0.0020Fits in one request
Mistral Small 3$0.0027Exceeds the context window

Llama 3.2 1B Instruct costs less

Agent loop

200K input + 10K output tokens

Llama 3.2 1B Instruct$0.0074Exceeds the context window
Mistral Small 3$0.011Exceeds the context window

Llama 3.2 1B 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 1B Instruct and Mistral Small 3
SpecificationMeta Llama 3.2 1B InstructMistral Small 3
MakerMeta LlamaMistral AI
WeightsOpen weightsOpen weights
ReleasedSeptember 25, 2024January 30, 2025
Context window60K33K
Input $/Mtok$0.027$0.05
Output $/Mtok$0.201$0.08
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.2 1B Instruct better than Mistral Small 3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.2 1B Instruct for a larger context window (60K against 33K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, Llama 3.2 1B Instruct or Mistral Small 3?

Llama 3.2 1B Instruct costs $0.027 per million input tokens and $0.201 per million output tokens; Mistral Small 3 costs $0.05 and $0.08. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.2 1B Instruct or Mistral Small 3?

Llama 3.2 1B Instruct, with 60K tokens against 33K.

How many benchmarks is the Llama 3.2 1B Instruct vs Mistral Small 3 comparison based on?

33 benchmarks have a result for both models as of October 21, 2026. Llama 3.2 1B Instruct's coding index rests on 0 independent benchmarks and Mistral Small 3's on 0. Where only one model has a result, the page says so instead of naming a winner.

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