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Command R (08-2024) vs Qwen3.5-122B-A10B

Command R (08-2024) costs 3.5x less per output token than Qwen3.5-122B-A10B ($0.60 vs $2.08 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
Qwen3.5-122B-A10BQwen
Coding
No data
Overall
No data
Output $/M
$2.08
25
vs boards won of 25 shared

Command R (08-2024) or Qwen3.5-122B-A10B: which to pick

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

Pick Command R (08-2024) for output tokens 3.5x cheaper ($0.60 vs $2.08 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
25
Command R (08-2024) only
0
Qwen3.5-122B-A10B 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, Qwen3.5-122B-A10B not benchmarked.
Widest category
Coding, 40.7 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: expert: Command R (08-2024) 1173 against Qwen3.5-122B-A10B 1431, 42.9 points apart on a 0 to 100 scale.
Output price
Command R (08-2024) $0.60 against Qwen3.5-122B-A10B $2.08 per million output tokens, 3.5x apart.
Context window
Command R (08-2024) takes 128K tokens, Qwen3.5-122B-A10B 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
CategoryCommand R (08-2024)BarsQwen3.5-122B-A10BTies
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 Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
LMArena WebDevNot measured1361Only Qwen3.5-122B-A10B measured
AA Coding IndexNot measured43.3Only Qwen3.5-122B-A10B measured
SciCodeNot measured39.7%Only Qwen3.5-122B-A10B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured31.1%Only Qwen3.5-122B-A10B measured
LMArena Text: coding11871436Qwen3.5-122B-A10B
LMArena Text: software and IT11971436Qwen3.5-122B-A10B
LMArena WebDev: ReactNot measured1353Only Qwen3.5-122B-A10B measured
LMArena WebDev: HTMLNot measured1351Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 31 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Command R (08-2024) and Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
AA Intelligence IndexNot measured17.7Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Command R (08-2024) and Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
τ²-Bench TelecomNot measured93.6%Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Command R (08-2024) and Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
GPQA Diamond (Artificial Analysis run)Not measured85.7%Only Qwen3.5-122B-A10B measured
Humanity's Last Exam (Artificial Analysis run)Not measured25.2%Only Qwen3.5-122B-A10B measured
Mystery game puzzlesNot measured17.0%Only Qwen3.5-122B-A10B measured
LMArena Text: hard prompts11861421Qwen3.5-122B-A10B
LMArena Text: expert11731431Qwen3.5-122B-A10B
LMArena Text: hard prompts in English11941431Qwen3.5-122B-A10B
LMArena Vision: diagramsNot measured1249Only Qwen3.5-122B-A10B measured
LMArena Vision: homeworkNot measured1261Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Command R (08-2024) and Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
LMArena Text: math11881431Qwen3.5-122B-A10B
LMArena Text: mathematical work11981431Qwen3.5-122B-A10B
Neither model has a result on the other 11 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Command R (08-2024) and Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
LMArena Text: science12521432Qwen3.5-122B-A10B
LMArena Text: medicine and healthcare12381423Qwen3.5-122B-A10B
LMArena Text: legal and government12681422Qwen3.5-122B-A10B
LMArena Text: business and finance12151414Qwen3.5-122B-A10B
Neither model has a result on the other 14 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 Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for Command R (08-2024) and Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
IFBenchNot measured75.7%Only Qwen3.5-122B-A10B measured
Long context reasoning (AA-LCR)Not measured76.3%Only Qwen3.5-122B-A10B measured
DTBenchNot measured84.3%Only Qwen3.5-122B-A10B measured
LMCANot measured32.2%Only Qwen3.5-122B-A10B measured
LMArena Text12291417Qwen3.5-122B-A10B
LMArena Text: instruction following11971399Qwen3.5-122B-A10B
LMArena Text: creative writing12341368Qwen3.5-122B-A10B
LMArena VisionNot measured1244Only Qwen3.5-122B-A10B measured
LMArena Text: English12381428Qwen3.5-122B-A10B
LMArena Text: non-English12161401Qwen3.5-122B-A10B
LMArena Text: Chinese12271463Qwen3.5-122B-A10B
LMArena Text: German12161425Qwen3.5-122B-A10B
LMArena Text: Japanese11661367Qwen3.5-122B-A10B
LMArena Text: Korean11621353Qwen3.5-122B-A10B
LMArena Text: FrenchNot measured1443Only Qwen3.5-122B-A10B measured
LMArena Text: SpanishNot measured1425Only Qwen3.5-122B-A10B measured
LMArena Text: Russian12271400Qwen3.5-122B-A10B
LMArena Text: PolishNot measured1398Only Qwen3.5-122B-A10B measured
LMArena Text: multi-turn12131416Qwen3.5-122B-A10B
LMArena Text: longer queries12301410Qwen3.5-122B-A10B
LMArena Text: writing and language12411387Qwen3.5-122B-A10B
LMArena Text: entertainment and media12231366Qwen3.5-122B-A10B
LMArena Vision: EnglishNot measured1249Only Qwen3.5-122B-A10B measured
LMArena Vision: ChineseNot measured1301Only Qwen3.5-122B-A10B measured
LMArena Vision: reading textNot measured1251Only Qwen3.5-122B-A10B measured
LMArena Vision: humorNot measured1243Only Qwen3.5-122B-A10B measured
LMArena Vision: creative writingNot measured1220Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 19 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 Qwen3.5-122B-A10B
BenchmarkCommand R (08-2024)Qwen3.5-122B-A10BLeader
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
Qwen3.5-122B-A10B$0.0013Fits in one request

Command R (08-2024) costs less

Repository review

50K input + 3K output tokens

Command R (08-2024)$0.0093Fits in one request
Qwen3.5-122B-A10B$0.019Fits 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
Qwen3.5-122B-A10B$0.073Fits 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 Qwen3.5-122B-A10B
SpecificationCohere Command R (08-2024)Qwen3.5-122B-A10B
MakerCohereQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 30, 2024February 25, 2026
Context window128K262K
Input $/Mtok$0.15$0.26
Output $/Mtok$0.60$2.08
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command R (08-2024) better than Qwen3.5-122B-A10B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command R (08-2024) for output tokens 3.5x cheaper ($0.60 vs $2.08 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Command R (08-2024) or Qwen3.5-122B-A10B?

Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for neither of them.

Which has the bigger context window, Command R (08-2024) or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B, with 262K tokens against 128K.

How many benchmarks is the Command R (08-2024) vs Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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