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Llama 3.2 1B Instruct vs Mistral Medium 3.5

Mistral Medium 3.5 leads Llama 3.2 1B Instruct on the Artificial Analysis Intelligence Index, 14.2 to 4.8, and Llama 3.2 1B Instruct costs 37.3x less per output token ($0.201 vs $7.50 per million). Updated October 21, 2026; 30 benchmarks have a result for both.

Replace Llama 3.2 1B Instruct Replace Mistral Medium 3.5
Llama 3.2 1B InstructMeta Llama
Coding
No data
Overall
4.8
Output $/M
$0.201
0
Mistral Medium 3.5Mistral AI
Coding
25.5
Overall
14.2
Output $/M
$7.50
30
vs boards won of 30 shared

Llama 3.2 1B Instruct or Mistral Medium 3.5: which to pick

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Llama 3.2 1B Instruct has none, so the two cannot be ranked on coding.

Pick Llama 3.2 1B Instruct for output tokens 37.3x cheaper ($0.201 vs $7.50 per million).

Model ALlama 3.2 1B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Medium 3.5Mistral AI25.5/1003 independent benchmarks$6.02 per solved task
Shared results
30
Llama 3.2 1B Instruct only
7
Mistral Medium 3.5 only
50
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 Medium 3.5 25.5 from 3 benchmarks.
Widest category
Agentic work, 94.2 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Llama 3.2 1B Instruct 0.0% against Mistral Medium 3.5 94.2%, 94.2 points apart on a 0 to 100 scale.
Output price
Llama 3.2 1B Instruct $0.201 against Mistral Medium 3.5 $7.50 per million output tokens, 37.3x apart.
Context window
Llama 3.2 1B Instruct takes 60K tokens, Mistral Medium 3.5 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
CategoryLlama 3.2 1B InstructBarsMistral Medium 3.5Ties
Coding03
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge04
General014
All shared boards030
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
LMArena WebDevNot measured1264Only Mistral Medium 3.5 measured
AA Coding IndexNot measured46.9Only Mistral Medium 3.5 measured
SWE-bench Verified (Vals AI)Not measured66.4%Only Mistral Medium 3.5 measured
Vibe Code Bench (Vals AI)Not measured2.9%Only Mistral Medium 3.5 measured
Code migration (Vals AI)Not measured5.1%Only Mistral Medium 3.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured39.0%Only Mistral Medium 3.5 measured
LiveCodeBench (Artificial Analysis run)1.9%Not measuredOnly Llama 3.2 1B Instruct measured
SciCodeNot measured40.2%Only Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)0.0%33.3%Mistral Medium 3.5
ALE-BenchNot measured764.0Only Mistral Medium 3.5 measured
LMArena Text: coding10701460Mistral Medium 3.5
LMArena Text: software and IT10561458Mistral Medium 3.5
LMArena WebDev: ReactNot measured1254Only Mistral Medium 3.5 measured
LMArena WebDev: HTMLNot measured1308Only Mistral Medium 3.5 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
AA Intelligence Index4.814.2Mistral Medium 3.5
Epoch Capabilities IndexNot measured141.4Only Mistral Medium 3.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
AA Agentic IndexNot measured7.0Only Mistral Medium 3.5 measured
Finance Agent (Vals AI)Not measured32.1%Only Mistral Medium 3.5 measured
Tax Agent Bench (Vals AI)Not measured4.5%Only Mistral Medium 3.5 measured
Legal Research Bench (Vals AI)Not measured9.1%Only Mistral Medium 3.5 measured
Excel Modeling Benchmark (Vals AI)Not measured11.2%Only Mistral Medium 3.5 measured
τ²-Bench Telecom0.0%94.2%Mistral Medium 3.5
BALROG6.6%Not measuredOnly Llama 3.2 1B Instruct measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
GPQA DiamondNot measured34.9%Only Mistral Medium 3.5 measured
GPQA Diamond (Artificial Analysis run)19.6%74.8%Mistral Medium 3.5
Humanity's Last Exam (Artificial Analysis run)5.5%13.8%Mistral Medium 3.5
GPQA Diamond (Epoch AI run)23.9%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: hard prompts10441436Mistral Medium 3.5
LMArena Text: expert10071432Mistral Medium 3.5
LMArena Text: hard prompts in English10871445Mistral Medium 3.5
LMArena Vision: diagramsNot measured1254Only Mistral Medium 3.5 measured
LMArena Vision: homeworkNot measured1230Only Mistral Medium 3.5 measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
AA Math Index0.0Not measuredOnly Llama 3.2 1B Instruct measured
AIME 2025 (Artificial Analysis run)0.0%Not measuredOnly Llama 3.2 1B Instruct measured
OTIS Mock AIME0.6%Not measuredOnly Llama 3.2 1B Instruct measured
ProofBenchNot measured9.0%Only Mistral Medium 3.5 measured
LMArena Text: math10861431Mistral Medium 3.5
LMArena Text: mathematical work10981440Mistral Medium 3.5
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 Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
MMLU ProNot measured75.3%Only Mistral Medium 3.5 measured
CaseLaw (Vals AI)Not measured44.2%Only Mistral Medium 3.5 measured
CorpFin (Vals AI)Not measured58.8%Only Mistral Medium 3.5 measured
TaxEval (Vals AI)Not measured68.0%Only Mistral Medium 3.5 measured
MortgageTax (Vals AI)Not measured28.9%Only Mistral Medium 3.5 measured
MedCode (Vals AI)Not measured33.8%Only Mistral Medium 3.5 measured
MMLU Pro (Artificial Analysis run)20.0%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: science10551428Mistral Medium 3.5
LMArena Text: medicine and healthcare10091409Mistral Medium 3.5
LMArena Text: legal and government10711437Mistral Medium 3.5
LMArena Text: business and finance10001426Mistral Medium 3.5
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
Design Arena: websitesNot measured1142Only Mistral Medium 3.5 measured
Design Arena: UI componentsNot measured1079Only Mistral Medium 3.5 measured
Design Arena: game devNot measured1079Only Mistral Medium 3.5 measured
Design Arena: data vizNot measured1120Only Mistral Medium 3.5 measured
Design Arena: 3DNot measured1061Only Mistral Medium 3.5 measured
Design Arena: all code categoriesNot measured1121Only Mistral Medium 3.5 measured
Design Arena: SVGNot measured950Only Mistral Medium 3.5 measured
Design Arena: ASCII artNot measured1063Only Mistral Medium 3.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for Llama 3.2 1B Instruct and Mistral Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
SAGE (Vals AI)Not measured37.6%Only Mistral Medium 3.5 measured
MedScribe (Vals AI)Not measured67.7%Only Mistral Medium 3.5 measured
Vals Multimodal IndexNot measured34.8%Only Mistral Medium 3.5 measured
IFBench22.8%68.8%Mistral Medium 3.5
Long context reasoning (AA-LCR)6.7%69.3%Mistral Medium 3.5
DTBenchNot measured75.5%Only Mistral Medium 3.5 measured
LMCANot measured26.1%Only Mistral Medium 3.5 measured
Surface Evolver BenchNot measured26.9%Only Mistral Medium 3.5 measured
LMArena Text10551421Mistral Medium 3.5
LMArena Text: instruction following10311415Mistral Medium 3.5
LMArena Text: creative writing10331374Mistral Medium 3.5
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: English11171433Mistral Medium 3.5
LMArena Text: non-English9731404Mistral Medium 3.5
LMArena Text: Chinese9591444Mistral Medium 3.5
LMArena Text: German10141453Mistral Medium 3.5
LMArena Text: KoreanNot measured1384Only Mistral Medium 3.5 measured
LMArena Text: FrenchNot measured1448Only Mistral Medium 3.5 measured
LMArena Text: SpanishNot measured1411Only Mistral Medium 3.5 measured
LMArena Text: Russian9411395Mistral Medium 3.5
LMArena Text: PolishNot measured1430Only Mistral Medium 3.5 measured
LMArena Text: multi-turn10301423Mistral Medium 3.5
LMArena Text: longer queries10501415Mistral Medium 3.5
LMArena Text: writing and language10301384Mistral Medium 3.5
LMArena Text: entertainment and media10251382Mistral Medium 3.5
LMArena Vision: EnglishNot measured1240Only Mistral Medium 3.5 measured
LMArena Vision: ChineseNot measured1244Only Mistral Medium 3.5 measured
LMArena Vision: reading textNot measured1233Only Mistral Medium 3.5 measured
LMArena Vision: humorNot measured1216Only Mistral Medium 3.5 measured
LMArena Vision: creative writingNot measured1198Only Mistral Medium 3.5 measured
Neither model has a result on the other 16 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 Medium 3.5
BenchmarkLlama 3.2 1B InstructMistral Medium 3.5Leader
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 Medium 3.5$0.0053Fits in one request

Llama 3.2 1B Instruct costs less

Repository review

50K input + 3K output tokens

Llama 3.2 1B Instruct$0.0020Fits in one request
Mistral Medium 3.5$0.098Fits in one request

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 Medium 3.5$0.375Fits in one request

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 Medium 3.5
SpecificationMeta Llama 3.2 1B InstructMistral Medium 3.5
MakerMeta LlamaMistral AI
WeightsOpen weightsNo public weights listed
ReleasedSeptember 25, 2024April 30, 2026
Context window60K262K
Input $/Mtok$0.027$1.50
Output $/Mtok$0.201$7.50
Coding indexNot benchmarked25.5
Independent measurements behind it03
Cost per solved taskNot computable$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.2 1B Instruct better than Mistral Medium 3.5 for coding?

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Llama 3.2 1B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.2 1B Instruct for output tokens 37.3x cheaper ($0.201 vs $7.50 per million).

Which is cheaper, Llama 3.2 1B Instruct or Mistral Medium 3.5?

Llama 3.2 1B Instruct costs $0.027 per million input tokens and $0.201 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Cost per solved task is known for Mistral Medium 3.5 only.

Which has the bigger context window, Llama 3.2 1B Instruct or Mistral Medium 3.5?

Mistral Medium 3.5, with 262K tokens against 60K.

How many benchmarks is the Llama 3.2 1B Instruct vs Mistral Medium 3.5 comparison based on?

30 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 Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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