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Llama 4 Scout vs Qwen3.7 Plus

Qwen3.7 Plus leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 25.2 to 6.5, and Llama 4 Scout costs 2.6x less per output token ($0.50 vs $1.28 per million). Updated October 21, 2026; 58 benchmarks have a result for both.

Replace Llama 4 Scout Replace Qwen3.7 Plus
Llama 4 ScoutMeta Llama
Coding
No data
Overall
24.9
Output $/M
$0.50
0
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
58
vs boards won of 58 shared

Llama 4 Scout or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Llama 4 Scout has none, so the two cannot be ranked on coding.

Pick Llama 4 Scout for output tokens 2.6x cheaper ($0.50 vs $1.28 per million) and a larger context window (1.31M against 1M tokens).

Model ALlama 4 ScoutMeta LlamaNot benchmarkedNo coding benchmark$1.276 per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
58
Llama 4 Scout only
24
Qwen3.7 Plus only
17
Like-for-like categories
8 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 4 Scout not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Web design, 59.0 points apart on average over 5 shared benchmarks.
Widest single gap
OTIS Mock AIME: Llama 4 Scout 7.8% against Qwen3.7 Plus 93.3%, 85.6 points apart on a 0 to 100 scale.
Output price
Llama 4 Scout $0.50 against Qwen3.7 Plus $1.28 per million output tokens, 2.6x apart.
Context window
Llama 4 Scout takes 1.31M tokens, Qwen3.7 Plus 1M.

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 4 ScoutBarsQwen3.7 PlusTies
Coding05
Intelligence02
Agentic work02
Reasoning08
Math03
Knowledge05
Web design05
General028
All shared boards058
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
SWE-bench Verified9.1%Not measuredOnly Llama 4 Scout measured
AA Coding Index8.255.9Qwen3.7 Plus
LiveCodeBench (Vals AI)38.5%Not measuredOnly Llama 4 Scout measured
Vibe Code Bench (Vals AI)Not measured46.4%Only Qwen3.7 Plus measured
Code migration (Vals AI)Not measured12.9%Only Qwen3.7 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
LiveCodeBench (Artificial Analysis run)29.9%Not measuredOnly Llama 4 Scout measured
SciCode21.3%46.1%Qwen3.7 Plus
Terminal-Bench Hard (Artificial Analysis run)1.5%47.0%Qwen3.7 Plus
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
LMArena Text: coding12861473Qwen3.7 Plus
LMArena Text: software and IT12861473Qwen3.7 Plus
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
AA Intelligence Index6.525.2Qwen3.7 Plus
Epoch Capabilities Index129.6147.0Qwen3.7 Plus
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
AA Agentic Index0.517.5Qwen3.7 Plus
Finance Agent (Vals AI)Not measured38.2%Only Qwen3.7 Plus measured
Tax Agent Bench (Vals AI)Not measured10.5%Only Qwen3.7 Plus measured
Legal Research Bench (Vals AI)Not measured16.4%Only Qwen3.7 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured49.3%Only Qwen3.7 Plus measured
τ²-Bench Telecom15.5%93.0%Qwen3.7 Plus
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Berkeley Function Calling Leaderboard (BFCL)28.1%Not measuredOnly Llama 4 Scout measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
GPQA Diamond47.0%Not measuredOnly Llama 4 Scout measured
MMMU Pro (Vals AI)58.8%Not measuredOnly Llama 4 Scout measured
GPQA Diamond (Artificial Analysis run)58.7%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)3.8%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)51.8%87.9%Qwen3.7 Plus
ARC-AGI0.5%Not measuredOnly Llama 4 Scout measured
ARC-AGI-20.0%Not measuredOnly Llama 4 Scout measured
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts12661460Qwen3.7 Plus
LMArena Text: expert12351466Qwen3.7 Plus
LMArena Text: hard prompts in English12931460Qwen3.7 Plus
LMArena Vision: diagrams11251292Qwen3.7 Plus
LMArena Vision: homework11481295Qwen3.7 Plus
Kagi LLM Benchmark36.9%Not measuredOnly Llama 4 Scout measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
AIME19.0%Not measuredOnly Llama 4 Scout measured
MATH 500 (Vals AI)79.2%Not measuredOnly Llama 4 Scout measured
MGSM (Vals AI)88.0%Not measuredOnly Llama 4 Scout measured
AA Math Index14.0Not measuredOnly Llama 4 Scout measured
AIME 2025 (Artificial Analysis run)14.0%Not measuredOnly Llama 4 Scout measured
OTIS Mock AIME7.8%93.3%Qwen3.7 Plus
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
MATH level 562.3%Not measuredOnly Llama 4 Scout measured
LMArena Text: math12871467Qwen3.7 Plus
LMArena Text: mathematical work12861470Qwen3.7 Plus
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
MMLU Pro69.6%Not measuredOnly Llama 4 Scout measured
LegalBench (Vals AI)72.0%Not measuredOnly Llama 4 Scout measured
CorpFin (Vals AI)46.8%Not measuredOnly Llama 4 Scout measured
TaxEval (Vals AI)55.2%Not measuredOnly Llama 4 Scout measured
MortgageTax (Vals AI)57.8%66.2%Qwen3.7 Plus
MedQA (Vals AI)50.9%Not measuredOnly Llama 4 Scout measured
MedCode (Vals AI)23.3%Not measuredOnly Llama 4 Scout measured
MMLU Pro (Artificial Analysis run)75.2%Not measuredOnly Llama 4 Scout measured
LMArena Text: science12781464Qwen3.7 Plus
LMArena Text: medicine and healthcare12751464Qwen3.7 Plus
LMArena Text: legal and government12851451Qwen3.7 Plus
LMArena Text: business and finance12571435Qwen3.7 Plus
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index05
Web design benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
Design Arena: websites7501269Qwen3.7 Plus
Design Arena: UI components7681261Qwen3.7 Plus
Design Arena: game dev7731262Qwen3.7 Plus
Design Arena: data viz8961276Qwen3.7 Plus
Design Arena: 3DNot measured1239Only Qwen3.7 Plus measured
Design Arena: all code categories7901269Qwen3.7 Plus
Design Arena: SVGNot measured1208Only Qwen3.7 Plus measured
Design Arena: ASCII artNot measured1143Only Qwen3.7 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index028
General benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
SAGE (Vals AI)34.8%39.3%Qwen3.7 Plus
MedScribe (Vals AI)50.6%Not measuredOnly Llama 4 Scout measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench39.5%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)27.7%73.0%Qwen3.7 Plus
DTBench57.9%84.0%Qwen3.7 Plus
LMCA12.0%37.6%Qwen3.7 Plus
Fiction.LiveBench36.0%Not measuredOnly Llama 4 Scout measured
LMArena Text12791454Qwen3.7 Plus
LMArena Text: instruction following12481439Qwen3.7 Plus
LMArena Text: creative writing12491438Qwen3.7 Plus
LMArena Vision11181278Qwen3.7 Plus
LMArena Text: English13041458Qwen3.7 Plus
LMArena Text: non-English12521445Qwen3.7 Plus
LMArena Text: Chinese12551509Qwen3.7 Plus
LMArena Text: German12731471Qwen3.7 Plus
LMArena Text: Japanese12061412Qwen3.7 Plus
LMArena Text: Korean12071413Qwen3.7 Plus
LMArena Text: French12831472Qwen3.7 Plus
LMArena Text: Spanish12781457Qwen3.7 Plus
LMArena Text: Russian12631457Qwen3.7 Plus
LMArena Text: Polish12651449Qwen3.7 Plus
LMArena Text: multi-turn12801459Qwen3.7 Plus
LMArena Text: longer queries12651454Qwen3.7 Plus
LMArena Text: writing and language12691437Qwen3.7 Plus
LMArena Text: entertainment and media12421422Qwen3.7 Plus
LMArena Vision: English11431280Qwen3.7 Plus
LMArena Vision: Chinese11061332Qwen3.7 Plus
LMArena Vision: reading text11171288Qwen3.7 Plus
LMArena Vision: humor11021261Qwen3.7 Plus
LMArena Vision: creative writing11261258Qwen3.7 Plus
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Llama 4 Scout and Qwen3.7 Plus
BenchmarkLlama 4 ScoutQwen3.7 PlusLeader
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 4 Scout$0.0004Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

Llama 4 Scout costs less

Repository review

50K input + 3K output tokens

Llama 4 Scout$0.010Fits in one request
Qwen3.7 Plus$0.020Fits in one request

Llama 4 Scout costs less

Agent loop

200K input + 10K output tokens

Llama 4 Scout$0.040Fits in one request
Qwen3.7 Plus$0.077Fits in one request

Llama 4 Scout 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 4 Scout and Qwen3.7 Plus
SpecificationMeta Llama 4 ScoutQwen3.7 Plus
MakerMeta LlamaQwen
WeightsOpen weightsNo public weights listed
ReleasedApril 5, 2025June 3, 2026
Context window1.31M1M
Input $/Mtok$0.175$0.32
Output $/Mtok$0.50$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it02
Cost per solved task$1.276Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 4 Scout better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Llama 4 Scout has none, so the two cannot be ranked on coding. Pick Llama 4 Scout for output tokens 2.6x cheaper ($0.50 vs $1.28 per million) and a larger context window (1.31M against 1M tokens).

Which is cheaper, Llama 4 Scout or Qwen3.7 Plus?

Llama 4 Scout costs $0.175 per million input tokens and $0.50 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for Llama 4 Scout only.

Which has the bigger context window, Llama 4 Scout or Qwen3.7 Plus?

Llama 4 Scout, with 1.31M tokens against 1M.

How many benchmarks is the Llama 4 Scout vs Qwen3.7 Plus comparison based on?

58 benchmarks have a result for both models as of October 21, 2026. Llama 4 Scout's coding index rests on 0 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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