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Llama 3.2 3B Instruct vs Qwen3 30B A3B

Qwen3 30B A3B leads Llama 3.2 3B Instruct on the Artificial Analysis Intelligence Index, 7.6 to 5.7, and Llama 3.2 3B Instruct costs 1.5x less per output token ($0.3325 vs $0.50 per million). Updated October 22, 2026; 33 benchmarks have a result for both.

Replace Llama 3.2 3B Instruct Replace Qwen3 30B A3B
Llama 3.2 3B InstructMeta Llama
Coding
No data
Overall
No data
Output $/M
$0.3325
1
Qwen3 30B A3BQwen
Coding
No data
Overall
38.2
Output $/M
$0.50
32
vs boards won of 33 shared

Llama 3.2 3B Instruct or Qwen3 30B A3B: 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 1.5x cheaper ($0.3325 vs $0.50 per million) and a larger context window (131K against 41K tokens).

Model ALlama 3.2 3B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 30B A3BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
33
Llama 3.2 3B Instruct only
2
Qwen3 30B A3B only
19
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, Qwen3 30B A3B not benchmarked.
Widest category
Math, 53.8 points apart on average over 4 shared benchmarks.
Widest single gap
AA Math Index: Llama 3.2 3B Instruct 3.3 against Qwen3 30B A3B 72.3, 69.0 points apart on a 0 to 100 scale.
Output price
Llama 3.2 3B Instruct $0.3325 against Qwen3 30B A3B $0.50 per million output tokens, 1.5x apart.
Context window
Llama 3.2 3B Instruct takes 131K tokens, Qwen3 30B A3B 41K.

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 InstructBarsQwen3 30B A3BTies
Coding03
Intelligence01
Agentic work01
Reasoning05
Math04
Knowledge05
General113
All shared boards132
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Llama 3.2 3B Instruct and Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
LiveCodeBench (Artificial Analysis run)8.3%50.6%Qwen3 30B A3B
Terminal-Bench Hard (Artificial Analysis run)Not measured6.8%Only Qwen3 30B A3B measured
WeirdMLNot measured29.8%Only Qwen3 30B A3B measured
LMArena Text: coding10981337Qwen3 30B A3B
LMArena Text: software and IT11031340Qwen3 30B A3B
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 Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
AA Intelligence Index5.77.6Qwen3 30B A3B
Epoch Capabilities IndexNot measured137.3Only Qwen3 30B A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Llama 3.2 3B Instruct and Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
τ²-Bench Telecom21.1%26.0%Qwen3 30B A3B
BALROG10.1%Not measuredOnly Llama 3.2 3B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)21.9%Not measuredOnly Llama 3.2 3B Instruct measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Llama 3.2 3B Instruct and Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
GPQA Diamond (Artificial Analysis run)25.5%61.6%Qwen3 30B A3B
Humanity's Last Exam (Artificial Analysis run)5.3%6.2%Qwen3 30B A3B
GPQA Diamond (Epoch AI run)Not measured61.7%Only Qwen3 30B A3B measured
LMArena Text: hard prompts10951314Qwen3 30B A3B
LMArena Text: expert10901314Qwen3 30B A3B
LMArena Text: hard prompts in English11411329Qwen3 30B A3B
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 Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
AA Math Index3.372.3Qwen3 30B A3B
AIME 2025 (Artificial Analysis run)3.3%72.3%Qwen3 30B A3B
OTIS Mock AIMENot measured62.8%Only Qwen3 30B A3B measured
LMArena Text: math11261355Qwen3 30B A3B
LMArena Text: mathematical work11281363Qwen3 30B A3B
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 3B Instruct and Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
MMLU Pro (Artificial Analysis run)34.7%77.7%Qwen3 30B A3B
LMArena Text: science11061321Qwen3 30B A3B
LMArena Text: medicine and healthcare11041318Qwen3 30B A3B
LMArena Text: legal and government11151314Qwen3 30B A3B
LMArena Text: business and finance10741309Qwen3 30B A3B
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Llama 3.2 3B Instruct and Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
Design Arena: websitesNot measured954Only Qwen3 30B A3B measured
Design Arena: UI componentsNot measured943Only Qwen3 30B A3B measured
Design Arena: game devNot measured898Only Qwen3 30B A3B measured
Design Arena: data vizNot measured967Only Qwen3 30B A3B measured
Design Arena: all code categoriesNot measured941Only Qwen3 30B A3B measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index113
General benchmarks for Llama 3.2 3B Instruct and Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
IFBench26.2%41.5%Qwen3 30B A3B
Long context reasoning (AA-LCR)4.3%0.0%Llama 3.2 3B Instruct
DTBenchNot measured60.3%Only Qwen3 30B A3B measured
LMCANot measured15.8%Only Qwen3 30B A3B measured
Fiction.LiveBenchNot measured40.6%Only Qwen3 30B A3B measured
Creative writing (Lech Mazur)Not measured75.3%Only Qwen3 30B A3B measured
LMArena Text11101317Qwen3 30B A3B
LMArena Text: instruction following10891283Qwen3 30B A3B
LMArena Text: creative writing10941271Qwen3 30B A3B
LMArena Text: English11801335Qwen3 30B A3B
LMArena Text: non-English10191295Qwen3 30B A3B
LMArena Text: Chinese10171347Qwen3 30B A3B
LMArena Text: German10561307Qwen3 30B A3B
LMArena Text: JapaneseNot measured1254Only Qwen3 30B A3B measured
LMArena Text: KoreanNot measured1261Only Qwen3 30B A3B measured
LMArena Text: FrenchNot measured1352Only Qwen3 30B A3B measured
LMArena Text: SpanishNot measured1317Only Qwen3 30B A3B measured
LMArena Text: Russian9491291Qwen3 30B A3B
LMArena Text: PolishNot measured1299Only Qwen3 30B A3B measured
LMArena Text: multi-turn11051307Qwen3 30B A3B
LMArena Text: longer queries11001312Qwen3 30B A3B
LMArena Text: writing and language10961290Qwen3 30B A3B
LMArena Text: entertainment and media10831258Qwen3 30B A3B
Neither model has a result on the other 23 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 Qwen3 30B A3B
BenchmarkLlama 3.2 3B InstructQwen3 30B A3BLeader
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
Qwen3 30B A3B$0.0004Fits 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
Qwen3 30B A3B$0.0075Exceeds the context window

Llama 3.2 3B Instruct costs less

Agent loop

200K input + 10K output tokens

Llama 3.2 3B Instruct$0.013Exceeds the context window
Qwen3 30B A3B$0.029Exceeds 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 Qwen3 30B A3B
SpecificationMeta Llama 3.2 3B InstructQwen3 30B A3B
MakerMeta LlamaQwen
WeightsOpen weightsOpen weights
ReleasedSeptember 25, 2024April 28, 2025
Context window131K41K
Input $/Mtok$0.0505$0.12
Output $/Mtok$0.3325$0.50
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 Qwen3 30B A3B 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 1.5x cheaper ($0.3325 vs $0.50 per million) and a larger context window (131K against 41K tokens).

Which is cheaper, Llama 3.2 3B Instruct or Qwen3 30B A3B?

Llama 3.2 3B Instruct costs $0.0505 per million input tokens and $0.3325 per million output tokens; Qwen3 30B A3B costs $0.12 and $0.50. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.2 3B Instruct or Qwen3 30B A3B?

Llama 3.2 3B Instruct, with 131K tokens against 41K.

How many benchmarks is the Llama 3.2 3B Instruct vs Qwen3 30B A3B 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 Qwen3 30B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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