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Command R (08-2024) vs Llama 4 Scout

Llama 4 Scout costs 1.2x less per output token than Command R (08-2024) ($0.50 vs $0.60 per million). Updated October 22, 2026; 25 benchmarks have a result for both.

Command R (08-2024)Cohere
Coding
No data
Overall
No data
Output $/M
$0.60
0
Llama 4 ScoutMeta Llama
Coding
No data
Overall
24.9
Output $/M
$0.50
25
vs boards won of 25 shared

Command R (08-2024) or Llama 4 Scout: which to pick

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

Pick Command R (08-2024) for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
25
Command R (08-2024) only
0
Llama 4 Scout only
57
Like-for-like categories
5 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
Command R (08-2024) not benchmarked, Llama 4 Scout not benchmarked.
Widest category
Coding, 15.6 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: math: Command R (08-2024) 1188 against Llama 4 Scout 1287, 16.5 points apart on a 0 to 100 scale.
Output price
Command R (08-2024) $0.60 against Llama 4 Scout $0.50 per million output tokens, 1.2x apart.
Context window
Command R (08-2024) takes 128K tokens, Llama 4 Scout 1.31M.

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
CategoryCommand R (08-2024)BarsLlama 4 ScoutTies
Coding02
Reasoning03
Math02
Knowledge04
General014
All shared boards025
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
SWE-bench VerifiedNot measured9.1%Only Llama 4 Scout measured
AA Coding IndexNot measured8.2Only Llama 4 Scout measured
LiveCodeBench (Vals AI)Not measured38.5%Only Llama 4 Scout measured
LiveCodeBench (Artificial Analysis run)Not measured29.9%Only Llama 4 Scout measured
SciCodeNot measured21.3%Only Llama 4 Scout measured
Terminal-Bench Hard (Artificial Analysis run)Not measured1.5%Only Llama 4 Scout measured
LMArena Text: coding11871286Llama 4 Scout
LMArena Text: software and IT11971286Llama 4 Scout
Neither model has a result on the other 31 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
AA Intelligence IndexNot measured6.5Only Llama 4 Scout measured
Epoch Capabilities IndexNot measured129.6Only Llama 4 Scout measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
AA Agentic IndexNot measured0.5Only Llama 4 Scout measured
τ²-Bench TelecomNot measured15.5%Only Llama 4 Scout measured
Berkeley Function Calling Leaderboard (BFCL)Not measured28.1%Only Llama 4 Scout 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 Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
GPQA DiamondNot measured47.0%Only Llama 4 Scout measured
MMMU Pro (Vals AI)Not measured58.8%Only Llama 4 Scout measured
GPQA Diamond (Artificial Analysis run)Not measured58.7%Only Llama 4 Scout measured
Humanity's Last Exam (Artificial Analysis run)Not measured3.8%Only Llama 4 Scout measured
GPQA Diamond (Epoch AI run)Not measured51.8%Only Llama 4 Scout measured
ARC-AGINot measured0.5%Only Llama 4 Scout measured
ARC-AGI-2Not measured0.0%Only Llama 4 Scout measured
LMArena Text: hard prompts11861266Llama 4 Scout
LMArena Text: expert11731235Llama 4 Scout
LMArena Text: hard prompts in English11941293Llama 4 Scout
LMArena Vision: diagramsNot measured1125Only Llama 4 Scout measured
LMArena Vision: homeworkNot measured1148Only Llama 4 Scout measured
Kagi LLM BenchmarkNot measured36.9%Only Llama 4 Scout measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
AIMENot measured19.0%Only Llama 4 Scout measured
MATH 500 (Vals AI)Not measured79.2%Only Llama 4 Scout measured
MGSM (Vals AI)Not measured88.0%Only Llama 4 Scout measured
AA Math IndexNot measured14.0Only Llama 4 Scout measured
AIME 2025 (Artificial Analysis run)Not measured14.0%Only Llama 4 Scout measured
OTIS Mock AIMENot measured7.8%Only Llama 4 Scout measured
MATH level 5Not measured62.3%Only Llama 4 Scout measured
LMArena Text: math11881287Llama 4 Scout
LMArena Text: mathematical work11981286Llama 4 Scout
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
MMLU ProNot measured69.6%Only Llama 4 Scout measured
LegalBench (Vals AI)Not measured72.0%Only Llama 4 Scout measured
CorpFin (Vals AI)Not measured46.8%Only Llama 4 Scout measured
TaxEval (Vals AI)Not measured55.2%Only Llama 4 Scout measured
MortgageTax (Vals AI)Not measured57.8%Only Llama 4 Scout measured
MedQA (Vals AI)Not measured50.9%Only Llama 4 Scout measured
MedCode (Vals AI)Not measured23.3%Only Llama 4 Scout measured
MMLU Pro (Artificial Analysis run)Not measured75.2%Only Llama 4 Scout measured
LMArena Text: science12521278Llama 4 Scout
LMArena Text: medicine and healthcare12381275Llama 4 Scout
LMArena Text: legal and government12681285Llama 4 Scout
LMArena Text: business and finance12151257Llama 4 Scout
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
Design Arena: websitesNot measured750Only Llama 4 Scout measured
Design Arena: UI componentsNot measured765Only Llama 4 Scout measured
Design Arena: game devNot measured772Only Llama 4 Scout measured
Design Arena: data vizNot measured896Only Llama 4 Scout measured
Design Arena: all code categoriesNot measured789Only Llama 4 Scout measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
SAGE (Vals AI)Not measured34.8%Only Llama 4 Scout measured
MedScribe (Vals AI)Not measured50.6%Only Llama 4 Scout measured
IFBenchNot measured39.5%Only Llama 4 Scout measured
Long context reasoning (AA-LCR)Not measured27.7%Only Llama 4 Scout measured
DTBenchNot measured57.9%Only Llama 4 Scout measured
LMCANot measured12.0%Only Llama 4 Scout measured
Fiction.LiveBenchNot measured36.0%Only Llama 4 Scout measured
LMArena Text12291279Llama 4 Scout
LMArena Text: instruction following11971248Llama 4 Scout
LMArena Text: creative writing12341249Llama 4 Scout
LMArena VisionNot measured1118Only Llama 4 Scout measured
LMArena Text: English12381304Llama 4 Scout
LMArena Text: non-English12161252Llama 4 Scout
LMArena Text: Chinese12271255Llama 4 Scout
LMArena Text: German12161273Llama 4 Scout
LMArena Text: Japanese11661206Llama 4 Scout
LMArena Text: Korean11621207Llama 4 Scout
LMArena Text: FrenchNot measured1283Only Llama 4 Scout measured
LMArena Text: SpanishNot measured1278Only Llama 4 Scout measured
LMArena Text: Russian12271263Llama 4 Scout
LMArena Text: PolishNot measured1265Only Llama 4 Scout measured
LMArena Text: multi-turn12131280Llama 4 Scout
LMArena Text: longer queries12301265Llama 4 Scout
LMArena Text: writing and language12411269Llama 4 Scout
LMArena Text: entertainment and media12231242Llama 4 Scout
LMArena Vision: EnglishNot measured1143Only Llama 4 Scout measured
LMArena Vision: ChineseNot measured1106Only Llama 4 Scout measured
LMArena Vision: reading textNot measured1117Only Llama 4 Scout measured
LMArena Vision: humorNot measured1102Only Llama 4 Scout measured
LMArena Vision: creative writingNot measured1126Only Llama 4 Scout 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 Command R (08-2024) and Llama 4 Scout
BenchmarkCommand R (08-2024)Llama 4 ScoutLeader
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

Command R (08-2024)$0.0004Fits in one request
Llama 4 Scout$0.0004Fits in one request

Llama 4 Scout costs less

Repository review

50K input + 3K output tokens

Command R (08-2024)$0.0093Fits in one request
Llama 4 Scout$0.010Fits in one request

Command R (08-2024) costs less

Agent loop

200K input + 10K output tokens

Command R (08-2024)$0.036Exceeds the context window
Llama 4 Scout$0.040Fits in one request

Command R (08-2024) 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 Command R (08-2024) and Llama 4 Scout
SpecificationCohere Command R (08-2024)Meta Llama 4 Scout
MakerCohereMeta Llama
WeightsNo public weights listedOpen weights
ReleasedAugust 30, 2024April 5, 2025
Context window128K1.31M
Input $/Mtok$0.15$0.175
Output $/Mtok$0.60$0.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computable$1.276
SourceOpenRouter listingOpenRouter listing

Questions

Is Command R (08-2024) better than Llama 4 Scout for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command R (08-2024) for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Command R (08-2024) or Llama 4 Scout?

Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; Llama 4 Scout costs $0.175 and $0.50. Cost per solved task is known for Llama 4 Scout only.

Which has the bigger context window, Command R (08-2024) or Llama 4 Scout?

Llama 4 Scout, with 1.31M tokens against 128K.

How many benchmarks is the Command R (08-2024) vs Llama 4 Scout comparison based on?

25 benchmarks have a result for both models as of October 22, 2026. Command R (08-2024)'s coding index rests on 0 independent benchmarks and Llama 4 Scout's on 0. Where only one model has a result, the page says so instead of naming a winner.

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