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Command R (08-2024) vs Llama 3.1 8B Instruct

Llama 3.1 8B Instruct costs 7.5x less per output token than Command R (08-2024) ($0.08 vs $0.60 per million). Updated October 21, 2026; 25 benchmarks have a result for both.

Command R (08-2024)Cohere
Coding
No data
Overall
No data
Output $/M
$0.60
23
Llama 3.1 8B InstructMeta Llama
Coding
No data
Overall
17.9
Output $/M
$0.08
2
vs boards won of 25 shared

Command R (08-2024) or Llama 3.1 8B Instruct: 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: hard prompts in English, where it leads.

Shared results
25
Command R (08-2024) only
0
Llama 3.1 8B Instruct only
26
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 3.1 8B Instruct not benchmarked.
Widest category
General, 11.0 points apart on average over 14 shared benchmarks.
Widest single gap
LMArena Text: Korean: Command R (08-2024) 1162 against Llama 3.1 8B Instruct 1053, 18.3 points apart on a 0 to 100 scale.
Output price
Command R (08-2024) $0.60 against Llama 3.1 8B Instruct $0.08 per million output tokens, 7.5x apart.
Context window
Command R (08-2024) takes 128K tokens, Llama 3.1 8B Instruct 131K.

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 3.1 8B InstructTies
Coding11
Reasoning21
Math20
Knowledge40
General140
All shared boards232
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
Coding benchmarks for Command R (08-2024) and Llama 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
AA Coding IndexNot measured5.4Only Llama 3.1 8B Instruct measured
LiveCodeBench (Artificial Analysis run)Not measured11.6%Only Llama 3.1 8B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)Not measured0.8%Only Llama 3.1 8B Instruct measured
WeirdMLNot measured1.7%Only Llama 3.1 8B Instruct measured
LMArena Text: coding11871195Llama 3.1 8B Instruct
LMArena Text: software and IT11971195Command R (08-2024)
Neither model has a result on the other 33 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 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
AA Intelligence IndexNot measured6.9Only Llama 3.1 8B Instruct measured
Epoch Capabilities IndexNot measured116.5Only Llama 3.1 8B Instruct 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 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
τ²-Bench TelecomNot measured16.4%Only Llama 3.1 8B Instruct measured
BALROGNot measured15.1%Only Llama 3.1 8B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)Not measured25.8%Only Llama 3.1 8B Instruct measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
Reasoning benchmarks for Command R (08-2024) and Llama 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
GPQA Diamond (Artificial Analysis run)Not measured25.9%Only Llama 3.1 8B Instruct measured
Humanity's Last Exam (Artificial Analysis run)Not measured5.3%Only Llama 3.1 8B Instruct measured
GPQA Diamond (Epoch AI run)Not measured27.0%Only Llama 3.1 8B Instruct measured
LMArena Text: hard prompts11861175Command R (08-2024)
LMArena Text: expert11731144Command R (08-2024)
LMArena Text: hard prompts in English11941196Llama 3.1 8B Instruct
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Command R (08-2024) and Llama 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
AA Math IndexNot measured4.3Only Llama 3.1 8B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured4.3%Only Llama 3.1 8B Instruct measured
OTIS Mock AIMENot measured1.7%Only Llama 3.1 8B Instruct measured
MATH level 5Not measured22.9%Only Llama 3.1 8B Instruct measured
GSM8KNot measured82.4%Only Llama 3.1 8B Instruct measured
LMArena Text: math11881179Command R (08-2024)
LMArena Text: mathematical work11981180Command R (08-2024)
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Command R (08-2024) and Llama 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
MMLU Pro (Artificial Analysis run)Not measured47.6%Only Llama 3.1 8B Instruct measured
MMLUNot measured56.1%Only Llama 3.1 8B Instruct measured
LMArena Text: science12521193Command R (08-2024)
LMArena Text: medicine and healthcare12381182Command R (08-2024)
LMArena Text: legal and government12681206Command R (08-2024)
LMArena Text: business and finance12151166Command R (08-2024)
Neither model has a result on the other 12 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Command R (08-2024) and Llama 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index140
General benchmarks for Command R (08-2024) and Llama 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
IFBenchNot measured28.6%Only Llama 3.1 8B Instruct measured
Long context reasoning (AA-LCR)Not measured18.0%Only Llama 3.1 8B Instruct measured
DTBenchNot measured50.9%Only Llama 3.1 8B Instruct measured
LMCANot measured5.4%Only Llama 3.1 8B Instruct measured
PIQANot measured81.2%Only Llama 3.1 8B Instruct measured
LMArena Text12291187Command R (08-2024)
LMArena Text: instruction following11971159Command R (08-2024)
LMArena Text: creative writing12341154Command R (08-2024)
LMArena Text: English12381218Command R (08-2024)
LMArena Text: non-English12161148Command R (08-2024)
LMArena Text: Chinese12271151Command R (08-2024)
LMArena Text: German12161144Command R (08-2024)
LMArena Text: Japanese11661061Command R (08-2024)
LMArena Text: Korean11621053Command R (08-2024)
LMArena Text: FrenchNot measured1178Only Llama 3.1 8B Instruct measured
LMArena Text: SpanishNot measured1169Only Llama 3.1 8B Instruct measured
LMArena Text: Russian12271158Command R (08-2024)
LMArena Text: multi-turn12131172Command R (08-2024)
LMArena Text: longer queries12301181Command R (08-2024)
LMArena Text: writing and language12411162Command R (08-2024)
LMArena Text: entertainment and media12231145Command R (08-2024)
Neither model has a result on the other 25 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 3.1 8B Instruct
BenchmarkCommand R (08-2024)Llama 3.1 8B InstructLeader
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 3.1 8B Instruct$0.0001Fits in one request

Llama 3.1 8B Instruct costs less

Repository review

50K input + 3K output tokens

Command R (08-2024)$0.0093Fits in one request
Llama 3.1 8B Instruct$0.0027Fits in one request

Llama 3.1 8B Instruct costs less

Agent loop

200K input + 10K output tokens

Command R (08-2024)$0.036Exceeds the context window
Llama 3.1 8B Instruct$0.011Exceeds the context window

Llama 3.1 8B 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 Command R (08-2024) and Llama 3.1 8B Instruct
SpecificationCohere Command R (08-2024)Meta Llama 3.1 8B Instruct
MakerCohereMeta Llama
WeightsNo public weights listedOpen weights
ReleasedAugust 30, 2024July 23, 2024
Context window128K131K
Input $/Mtok$0.15$0.05
Output $/Mtok$0.60$0.08
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command R (08-2024) better than Llama 3.1 8B Instruct 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: hard prompts in English, where it leads.

Which is cheaper, Command R (08-2024) or Llama 3.1 8B Instruct?

Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; Llama 3.1 8B Instruct costs $0.05 and $0.08. Cost per solved task is known for neither of them.

Which has the bigger context window, Command R (08-2024) or Llama 3.1 8B Instruct?

Llama 3.1 8B Instruct, with 131K tokens against 128K.

How many benchmarks is the Command R (08-2024) vs Llama 3.1 8B Instruct comparison based on?

25 benchmarks have a result for both models as of October 21, 2026. Command R (08-2024)'s coding index rests on 0 independent benchmarks and Llama 3.1 8B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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