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Llama 3.2 3B Instruct vs MiniMax M2

MiniMax M2 leads Llama 3.2 3B Instruct on the Artificial Analysis Intelligence Index, 18.6 to 5.7, and Llama 3.2 3B Instruct costs 3.1x less per output token ($0.3325 vs $1.02 per million). Updated October 22, 2026; 33 benchmarks have a result for both.

Replace Llama 3.2 3B Instruct Replace MiniMax M2
Llama 3.2 3B InstructMeta Llama
Coding
No data
Overall
No data
Output $/M
$0.3325
0
MiniMax M2MiniMax
Coding
No data
Overall
No data
Output $/M
$1.02
33
vs boards won of 33 shared

Llama 3.2 3B Instruct or MiniMax M2: which to pick

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

Pick Llama 3.2 3B Instruct for output tokens 3.1x cheaper ($0.3325 vs $1.02 per million) and work measured by 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 BMiniMax M2MiniMaxNot benchmarked1 independent benchmark$0.702 per solved task
Shared results
33
Llama 3.2 3B Instruct only
2
MiniMax M2 only
17
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 3B Instruct not benchmarked, MiniMax M2 not benchmarked.
Widest category
Agentic work, 65.8 points apart on average over 1 shared benchmark.
Widest single gap
AA Math Index: Llama 3.2 3B Instruct 3.3 against MiniMax M2 78.3, 75.0 points apart on a 0 to 100 scale.
Output price
Llama 3.2 3B Instruct $0.3325 against MiniMax M2 $1.02 per million output tokens, 3.1x apart.
Context window
Llama 3.2 3B Instruct takes 131K tokens, MiniMax M2 205K.

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 InstructBarsMiniMax M2Ties
Coding03
Intelligence01
Agentic work01
Reasoning05
Math04
Knowledge05
General014
All shared boards033
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Llama 3.2 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
SWE-bench VerifiedNot measured61.0%Only MiniMax M2 measured
LMArena WebDevNot measured1297Only MiniMax M2 measured
LiveCodeBench (Artificial Analysis run)8.3%82.6%MiniMax M2
Terminal-Bench Hard (Artificial Analysis run)Not measured25.8%Only MiniMax M2 measured
Terminal-BenchNot measured30.0%Only MiniMax M2 measured
LMArena Text: coding10981371MiniMax M2
LMArena Text: software and IT11031373MiniMax M2
LMArena WebDev: HTMLNot measured1306Only MiniMax M2 measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Llama 3.2 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
AA Intelligence Index5.718.6MiniMax M2
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 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
τ²-Bench Telecom21.1%86.8%MiniMax M2
BALROG10.1%Not measuredOnly Llama 3.2 3B Instruct measured
Vending-Bench 2Not measured$161Only MiniMax M2 measured
Berkeley Function Calling Leaderboard (BFCL)21.9%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 index05
Reasoning benchmarks for Llama 3.2 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
GPQA Diamond (Artificial Analysis run)25.5%77.7%MiniMax M2
Humanity's Last Exam (Artificial Analysis run)5.3%13.7%MiniMax M2
LMArena Text: hard prompts10951357MiniMax M2
LMArena Text: expert10901338MiniMax M2
LMArena Text: hard prompts in English11411376MiniMax M2
Kagi LLM BenchmarkNot measured57.8%Only MiniMax M2 measured
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 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
AA Math Index3.378.3MiniMax M2
AIME 2025 (Artificial Analysis run)3.3%78.3%MiniMax M2
LMArena Text: math11261351MiniMax M2
LMArena Text: mathematical work11281368MiniMax M2
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 MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
MMLU Pro (Artificial Analysis run)34.7%82.0%MiniMax M2
LMArena Text: science11061348MiniMax M2
LMArena Text: medicine and healthcare11041367MiniMax M2
LMArena Text: legal and government11151349MiniMax M2
LMArena Text: business and finance10741336MiniMax M2
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Llama 3.2 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
Design Arena: websitesNot measured1143Only MiniMax M2 measured
Design Arena: UI componentsNot measured1137Only MiniMax M2 measured
Design Arena: game devNot measured1118Only MiniMax M2 measured
Design Arena: data vizNot measured1140Only MiniMax M2 measured
Design Arena: 3DNot measured1098Only MiniMax M2 measured
Design Arena: all code categoriesNot measured1135Only MiniMax M2 measured
Design Arena: SVGNot measured1100Only MiniMax M2 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for Llama 3.2 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
IFBench26.2%72.3%MiniMax M2
Long context reasoning (AA-LCR)4.3%64.3%MiniMax M2
LMArena Text11101340MiniMax M2
LMArena Text: instruction following10891329MiniMax M2
LMArena Text: creative writing10941286MiniMax M2
LMArena Text: English11801364MiniMax M2
LMArena Text: non-English10191313MiniMax M2
LMArena Text: Chinese10171366MiniMax M2
LMArena Text: German10561357MiniMax M2
LMArena Text: FrenchNot measured1336Only MiniMax M2 measured
LMArena Text: SpanishNot measured1326Only MiniMax M2 measured
LMArena Text: Russian9491330MiniMax M2
LMArena Text: PolishNot measured1312Only MiniMax M2 measured
LMArena Text: multi-turn11051361MiniMax M2
LMArena Text: longer queries11001331MiniMax M2
LMArena Text: writing and language10961295MiniMax M2
LMArena Text: entertainment and media10831298MiniMax M2
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 3B Instruct and MiniMax M2
BenchmarkLlama 3.2 3B InstructMiniMax M2Leader
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
MiniMax M2$0.0008Fits 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
MiniMax M2$0.016Fits 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
MiniMax M2$0.061Exceeds 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 MiniMax M2
SpecificationMeta Llama 3.2 3B InstructMiniMax M2
MakerMeta LlamaMiniMax
WeightsOpen weightsOpen weights
ReleasedSeptember 25, 2024October 23, 2025
Context window131K205K
Input $/Mtok$0.0505$0.255
Output $/Mtok$0.3325$1.02
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computable$0.702
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.2 3B Instruct better than MiniMax M2 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.2 3B Instruct for output tokens 3.1x cheaper ($0.3325 vs $1.02 per million) and work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, Llama 3.2 3B Instruct or MiniMax M2?

Llama 3.2 3B Instruct costs $0.0505 per million input tokens and $0.3325 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Cost per solved task is known for MiniMax M2 only.

Which has the bigger context window, Llama 3.2 3B Instruct or MiniMax M2?

MiniMax M2, with 205K tokens against 131K.

How many benchmarks is the Llama 3.2 3B Instruct vs MiniMax M2 comparison based on?

33 benchmarks have a result for both models as of October 22, 2026. Llama 3.2 3B Instruct's coding index rests on 0 independent benchmarks and MiniMax M2's on 1. Where only one model has a result, the page says so instead of naming a winner.

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