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Llama 3.2 1B Instruct vs Qwen3 Next 80B A3B Thinking

Qwen3 Next 80B A3B Thinking leads Llama 3.2 1B Instruct on the Artificial Analysis Intelligence Index, 11.2 to 4.8, and Llama 3.2 1B Instruct costs 6.0x less per output token ($0.201 vs $1.20 per million). Updated October 22, 2026; 24 benchmarks have a result for both.

Llama 3.2 1B InstructMeta Llama
Coding
No data
Overall
9.6
Output $/M
$0.201
0
Qwen3 Next 80B A3B ThinkingQwen
Coding
No data
Overall
No data
Output $/M
$1.20
24
vs boards won of 24 shared

Llama 3.2 1B Instruct or Qwen3 Next 80B A3B Thinking: 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 output tokens 6.0x cheaper ($0.201 vs $1.20 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
24
Llama 3.2 1B Instruct only
14
Qwen3 Next 80B A3B Thinking only
6
Like-for-like categories
6 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, Qwen3 Next 80B A3B Thinking not benchmarked.
Widest category
Knowledge, 56.9 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena Text: Chinese: Llama 3.2 1B Instruct 959 against Qwen3 Next 80B A3B Thinking 1407, 67.8 points apart on a 0 to 100 scale.
Output price
Llama 3.2 1B Instruct $0.201 against Qwen3 Next 80B A3B Thinking $1.20 per million output tokens, 6.0x apart.
Context window
Llama 3.2 1B Instruct takes 60K tokens, Qwen3 Next 80B A3B Thinking 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 InstructBarsQwen3 Next 80B A3B ThinkingTies
Coding02
Intelligence01
Reasoning03
Math02
Knowledge04
General012
All shared boards024
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Llama 3.2 1B Instruct and Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
AA Coding IndexNot measured17.4Only Qwen3 Next 80B A3B Thinking measured
LiveCodeBench (Artificial Analysis run)1.9%Not measuredOnly Llama 3.2 1B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)0.0%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: coding10701392Qwen3 Next 80B A3B Thinking
LMArena Text: software and IT10561393Qwen3 Next 80B A3B Thinking
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 1B Instruct and Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
AA Intelligence Index4.811.2Qwen3 Next 80B A3B Thinking
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Llama 3.2 1B Instruct and Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
τ²-Bench Telecom0.0%Not measuredOnly Llama 3.2 1B Instruct measured
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 index03
Reasoning benchmarks for Llama 3.2 1B Instruct and Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
GPQA Diamond (Artificial Analysis run)19.6%Not measuredOnly Llama 3.2 1B Instruct measured
Humanity's Last Exam (Artificial Analysis run)5.5%Not measuredOnly Llama 3.2 1B Instruct measured
GPQA Diamond (Epoch AI run)23.9%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: hard prompts10441371Qwen3 Next 80B A3B Thinking
LMArena Text: expert10071376Qwen3 Next 80B A3B Thinking
LMArena Text: hard prompts in English10871384Qwen3 Next 80B A3B Thinking
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Llama 3.2 1B Instruct and Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
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
LMArena Text: math10861399Qwen3 Next 80B A3B Thinking
LMArena Text: mathematical work10981390Qwen3 Next 80B A3B Thinking
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Llama 3.2 1B Instruct and Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
MMLU Pro (Artificial Analysis run)20.0%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text: science10551384Qwen3 Next 80B A3B Thinking
LMArena Text: medicine and healthcare10091392Qwen3 Next 80B A3B Thinking
LMArena Text: legal and government10711364Qwen3 Next 80B A3B Thinking
LMArena Text: business and finance10001360Qwen3 Next 80B A3B Thinking
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 Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index012
General benchmarks for Llama 3.2 1B Instruct and Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
IFBench22.8%Not measuredOnly Llama 3.2 1B Instruct measured
Long context reasoning (AA-LCR)6.7%Not measuredOnly Llama 3.2 1B Instruct measured
LMArena Text10551368Qwen3 Next 80B A3B Thinking
LMArena Text: instruction following10311344Qwen3 Next 80B A3B Thinking
LMArena Text: creative writing10331314Qwen3 Next 80B A3B Thinking
LMArena Text: English11171392Qwen3 Next 80B A3B Thinking
LMArena Text: non-English9731342Qwen3 Next 80B A3B Thinking
LMArena Text: Chinese9591407Qwen3 Next 80B A3B Thinking
LMArena Text: German10141356Qwen3 Next 80B A3B Thinking
LMArena Text: JapaneseNot measured1280Only Qwen3 Next 80B A3B Thinking measured
LMArena Text: KoreanNot measured1310Only Qwen3 Next 80B A3B Thinking measured
LMArena Text: FrenchNot measured1351Only Qwen3 Next 80B A3B Thinking measured
LMArena Text: SpanishNot measured1358Only Qwen3 Next 80B A3B Thinking measured
LMArena Text: Russian9411337Qwen3 Next 80B A3B Thinking
LMArena Text: PolishNot measured1345Only Qwen3 Next 80B A3B Thinking measured
LMArena Text: multi-turn10301346Qwen3 Next 80B A3B Thinking
LMArena Text: longer queries10501353Qwen3 Next 80B A3B Thinking
LMArena Text: writing and language10301330Qwen3 Next 80B A3B Thinking
LMArena Text: entertainment and media10251312Qwen3 Next 80B A3B Thinking
Neither model has a result on the other 27 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 Qwen3 Next 80B A3B Thinking
BenchmarkLlama 3.2 1B InstructQwen3 Next 80B A3B ThinkingLeader
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
Qwen3 Next 80B A3B Thinking$0.0008Fits 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
Qwen3 Next 80B A3B Thinking$0.011Fits 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
Qwen3 Next 80B A3B Thinking$0.042Fits 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 Qwen3 Next 80B A3B Thinking
SpecificationMeta Llama 3.2 1B InstructQwen3 Next 80B A3B Thinking
MakerMeta LlamaQwen
WeightsOpen weightsOpen weights
ReleasedSeptember 25, 2024September 11, 2025
Context window60K262K
Input $/Mtok$0.027$0.15
Output $/Mtok$0.201$1.20
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 Qwen3 Next 80B A3B Thinking for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.2 1B Instruct for output tokens 6.0x cheaper ($0.201 vs $1.20 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Llama 3.2 1B Instruct or Qwen3 Next 80B A3B Thinking?

Llama 3.2 1B Instruct costs $0.027 per million input tokens and $0.201 per million output tokens; Qwen3 Next 80B A3B Thinking costs $0.15 and $1.20. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.2 1B Instruct or Qwen3 Next 80B A3B Thinking?

Qwen3 Next 80B A3B Thinking, with 262K tokens against 60K.

How many benchmarks is the Llama 3.2 1B Instruct vs Qwen3 Next 80B A3B Thinking comparison based on?

24 benchmarks have a result for both models as of October 22, 2026. Llama 3.2 1B Instruct's coding index rests on 0 independent benchmarks and Qwen3 Next 80B A3B Thinking's on 0. Where only one model has a result, the page says so instead of naming a winner.

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