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Command R (08-2024) vs Qwen3.5-Flash

Qwen3.5-Flash costs 2.3x less per output token than Command R (08-2024) ($0.26 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
Qwen3.5-FlashQwen
Coding
41.1
Overall
50.1
Output $/M
$0.26
25
vs boards won of 25 shared

Command R (08-2024) or Qwen3.5-Flash: which to pick

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Command R (08-2024) has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
25
Command R (08-2024) only
0
Qwen3.5-Flash only
30
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-Flash 41.1 from 2 benchmarks.
Widest category
Coding, 37.0 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: expert: Command R (08-2024) 1173 against Qwen3.5-Flash 1407, 39.0 points apart on a 0 to 100 scale.
Output price
Command R (08-2024) $0.60 against Qwen3.5-Flash $0.26 per million output tokens, 2.3x apart.
Context window
Command R (08-2024) takes 128K tokens, Qwen3.5-Flash 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
CategoryCommand R (08-2024)BarsQwen3.5-FlashTies
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-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
LMArena WebDevNot measured1244Only Qwen3.5-Flash measured
LiveCodeBench (Vals AI)Not measured83.3%Only Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)Not measured64.4%Only Qwen3.5-Flash measured
ALE-BenchNot measured265.9Only Qwen3.5-Flash measured
LMArena Text: coding11871412Qwen3.5-Flash
LMArena Text: software and IT11971416Qwen3.5-Flash
LMArena WebDev: ReactNot measured1229Only Qwen3.5-Flash measured
LMArena WebDev: HTMLNot measured1291Only Qwen3.5-Flash 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-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
Epoch Capabilities IndexNot measured143.5Only Qwen3.5-Flash measured
Neither model has a result on the other 1 board here
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Agentic work benchmarks for Command R (08-2024) and Qwen3.5-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
Neither model has a result on 41 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Command R (08-2024) and Qwen3.5-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
GPQA DiamondNot measured82.8%Only Qwen3.5-Flash measured
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
GPQA Diamond (Epoch AI run)Not measured82.3%Only Qwen3.5-Flash measured
Chess puzzlesNot measured14.0%Only Qwen3.5-Flash measured
Mystery game puzzlesNot measured20.0%Only Qwen3.5-Flash measured
LMArena Text: hard prompts11861403Qwen3.5-Flash
LMArena Text: expert11731407Qwen3.5-Flash
LMArena Text: hard prompts in English11941409Qwen3.5-Flash
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-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
AIMENot measured92.5%Only Qwen3.5-Flash measured
OTIS Mock AIMENot measured84.4%Only Qwen3.5-Flash measured
FrontierMath, tiers 1 to 3Not measured18.2%Only Qwen3.5-Flash measured
LMArena Text: math11881407Qwen3.5-Flash
LMArena Text: mathematical work11981413Qwen3.5-Flash
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 Command R (08-2024) and Qwen3.5-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
MMLU ProNot measured84.1%Only Qwen3.5-Flash measured
LegalBench (Vals AI)Not measured84.3%Only Qwen3.5-Flash measured
CaseLaw (Vals AI)Not measured56.0%Only Qwen3.5-Flash measured
CorpFin (Vals AI)Not measured63.6%Only Qwen3.5-Flash measured
TaxEval (Vals AI)Not measured72.2%Only Qwen3.5-Flash measured
MortgageTax (Vals AI)Not measured67.4%Only Qwen3.5-Flash measured
MedCode (Vals AI)Not measured33.0%Only Qwen3.5-Flash measured
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
LMArena Text: science12521415Qwen3.5-Flash
LMArena Text: medicine and healthcare12381407Qwen3.5-Flash
LMArena Text: legal and government12681398Qwen3.5-Flash
LMArena Text: business and finance12151394Qwen3.5-Flash
Neither model has a result on the other 6 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-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
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-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
SAGE (Vals AI)Not measured42.5%Only Qwen3.5-Flash measured
MedScribe (Vals AI)Not measured70.6%Only Qwen3.5-Flash measured
DTBenchNot measured82.9%Only Qwen3.5-Flash measured
LMCANot measured29.1%Only Qwen3.5-Flash measured
LMArena Text12291397Qwen3.5-Flash
LMArena Text: instruction following11971374Qwen3.5-Flash
LMArena Text: creative writing12341343Qwen3.5-Flash
LMArena Text: English12381404Qwen3.5-Flash
LMArena Text: non-English12161385Qwen3.5-Flash
LMArena Text: Chinese12271445Qwen3.5-Flash
LMArena Text: German12161390Qwen3.5-Flash
LMArena Text: Japanese11661369Qwen3.5-Flash
LMArena Text: Korean11621344Qwen3.5-Flash
LMArena Text: FrenchNot measured1413Only Qwen3.5-Flash measured
LMArena Text: SpanishNot measured1400Only Qwen3.5-Flash measured
LMArena Text: Russian12271380Qwen3.5-Flash
LMArena Text: PolishNot measured1376Only Qwen3.5-Flash measured
LMArena Text: multi-turn12131393Qwen3.5-Flash
LMArena Text: longer queries12301392Qwen3.5-Flash
LMArena Text: writing and language12411369Qwen3.5-Flash
LMArena Text: entertainment and media12231347Qwen3.5-Flash
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 Qwen3.5-Flash
BenchmarkCommand R (08-2024)Qwen3.5-FlashLeader
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-Flash$0.0002Fits in one request

Qwen3.5-Flash costs less

Repository review

50K input + 3K output tokens

Command R (08-2024)$0.0093Fits in one request
Qwen3.5-Flash$0.0040Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

Command R (08-2024)$0.036Exceeds the context window
Qwen3.5-Flash$0.016Fits in one request

Qwen3.5-Flash 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-Flash
SpecificationCohere Command R (08-2024)Qwen3.5-Flash
MakerCohereQwen
WeightsNo public weights listedNo public weights listed
ReleasedAugust 30, 2024February 25, 2026
Context window128K1M
Input $/Mtok$0.15$0.065
Output $/Mtok$0.60$0.26
Coding indexNot benchmarked41.1
Independent measurements behind it02
Cost per solved taskNot computable$0.40
SourceOpenRouter listingOpenRouter listing

Questions

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

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Command R (08-2024) has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

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

Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.

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

Qwen3.5-Flash, with 1M tokens against 128K.

How many benchmarks is the Command R (08-2024) vs Qwen3.5-Flash 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-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

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