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Command A vs Qwen3.5-Flash

Updated October 21, 2026. 41 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Command A Replace Qwen3.5-Flash
Command ACohere
Coding
No data
Overall
13.1
Output $/M
$10.00
1
Qwen3.5-FlashQwen
Coding
41.1
Overall
No data
Output $/M
$0.26
40
vs boards won of 41 shared

Decision reading

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

Command A has the edge where the benchmark that matters is CaseLaw (Vals AI), where it leads.

Model ACommand ACohereNot benchmarked1 independent benchmark$2.69 per solved taskModel BQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved task
Shared results
41
Command A only
19
Qwen3.5-Flash only
14
Like-for-like categories
5 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 A not benchmarked, Qwen3.5-Flash 41.1 from 2 benchmarks.
Widest category
Math, 37.9 points apart on average over 3 shared benchmarks.
Widest single gap
AIME: Command A 13.3% against Qwen3.5-Flash 92.5%, 79.2 points apart on a 0 to 100 scale.
Output price
Command A $10.00 against Qwen3.5-Flash $0.26 per million output tokens, 38.5x apart.
Context window
Command A takes 256K 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 ABarsQwen3.5-FlashTies
Coding04
Reasoning04
Math03
Knowledge19
General020
All shared boards140
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
LMArena WebDevNot measured1244Only Qwen3.5-Flash measured
AA Coding Index27.8Not measuredOnly Command A measured
LiveCodeBench (Vals AI)35.1%83.3%Qwen3.5-Flash
SWE-bench Verified (Vals AI)7.8%64.4%Qwen3.5-Flash
Terminal-Bench 2.1 (Vals AI)17.6%Not measuredOnly Command A measured
LiveCodeBench (Artificial Analysis run)28.7%Not measuredOnly Command A measured
SciCode38.5%Not measuredOnly Command A measured
Terminal-Bench Hard (Artificial Analysis run)25.0%Not measuredOnly Command A measured
ALE-BenchNot measured265.9Only Qwen3.5-Flash measured
LMArena Text: coding13301412Qwen3.5-Flash
LMArena Text: software and IT13361416Qwen3.5-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 25 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
AA Intelligence Index13.1Not measuredOnly Command A measured
Epoch Capabilities IndexNot measured143.5Only Qwen3.5-Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
AA Agentic Index1.0Not measuredOnly Command A measured
Finance Agent (Vals AI)9.0%Not measuredOnly Command A measured
τ²-Bench Telecom80.7%Not measuredOnly Command A measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
GPQA Diamond48.5%82.8%Qwen3.5-Flash
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
GPQA Diamond (Artificial Analysis run)76.1%Not measuredOnly Command A measured
Humanity's Last Exam (Artificial Analysis run)12.0%Not measuredOnly Command A 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 prompts13261403Qwen3.5-Flash
LMArena Text: expert12961407Qwen3.5-Flash
LMArena Text: hard prompts in English13351409Qwen3.5-Flash
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
AIME13.3%92.5%Qwen3.5-Flash
MATH 500 (Vals AI)76.2%Not measuredOnly Command A measured
MGSM (Vals AI)85.7%Not measuredOnly Command A measured
AA Math Index13.0Not measuredOnly Command A measured
AIME 2025 (Artificial Analysis run)13.0%Not measuredOnly Command A 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: math13001407Qwen3.5-Flash
LMArena Text: mathematical work13121413Qwen3.5-Flash
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index19
Knowledge benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
MMLU Pro69.2%84.1%Qwen3.5-Flash
LegalBench (Vals AI)79.7%84.3%Qwen3.5-Flash
CaseLaw (Vals AI)64.5%56.0%Command A
CorpFin (Vals AI)46.0%63.6%Qwen3.5-Flash
TaxEval (Vals AI)61.4%72.2%Qwen3.5-Flash
MortgageTax (Vals AI)Not measured67.4%Only Qwen3.5-Flash measured
MedQA (Vals AI)80.5%Not measuredOnly Command A measured
MedCode (Vals AI)19.7%33.0%Qwen3.5-Flash
MMLU Pro (Artificial Analysis run)71.2%Not measuredOnly Command A measured
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
LMArena Text: science13391415Qwen3.5-Flash
LMArena Text: medicine and healthcare13341407Qwen3.5-Flash
LMArena Text: legal and government13481398Qwen3.5-Flash
LMArena Text: business and finance13151394Qwen3.5-Flash
Neither model has a result on the other 3 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index020
General benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-FlashLeader
SAGE (Vals AI)Not measured42.5%Only Qwen3.5-Flash measured
MedScribe (Vals AI)55.7%70.6%Qwen3.5-Flash
IFBench73.9%Not measuredOnly Command A measured
Long context reasoning (AA-LCR)52.7%Not measuredOnly Command A measured
DTBench61.3%82.9%Qwen3.5-Flash
LMCA10.3%29.1%Qwen3.5-Flash
LMArena Text13311397Qwen3.5-Flash
LMArena Text: instruction following13091374Qwen3.5-Flash
LMArena Text: creative writing13191343Qwen3.5-Flash
LMArena Text: English13441404Qwen3.5-Flash
LMArena Text: non-English13131385Qwen3.5-Flash
LMArena Text: Chinese13271445Qwen3.5-Flash
LMArena Text: German13421390Qwen3.5-Flash
LMArena Text: Japanese12851369Qwen3.5-Flash
LMArena Text: Korean12851344Qwen3.5-Flash
LMArena Text: French13511413Qwen3.5-Flash
LMArena Text: Spanish13471400Qwen3.5-Flash
LMArena Text: Russian13141380Qwen3.5-Flash
LMArena Text: Polish13241376Qwen3.5-Flash
LMArena Text: multi-turn13381393Qwen3.5-Flash
LMArena Text: longer queries13341392Qwen3.5-Flash
LMArena Text: writing and language13281369Qwen3.5-Flash
LMArena Text: entertainment and media13061347Qwen3.5-Flash
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Command A and Qwen3.5-Flash
BenchmarkCommand AQwen3.5-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 A$0.0075Fits in one request
Qwen3.5-Flash$0.0002Fits in one request

Qwen3.5-Flash costs less

Repository review

50K input + 3K output tokens

Command A$0.155Fits in one request
Qwen3.5-Flash$0.0040Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

Command A$0.600Fits in one request
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 A and Qwen3.5-Flash
SpecificationCohere Command AQwen3.5-Flash
MakerCohereQwen
WeightsOpen weightsNo public weights listed
ReleasedMarch 13, 2025February 25, 2026
Context window256K1M
Input $/Mtok$2.50$0.065
Output $/Mtok$10.00$0.26
Coding indexNot benchmarked41.1
Independent measurements behind it12
Cost per solved task$2.69$0.40
SourceOpenRouter listingOpenRouter listing

Questions

Is Command A better than Qwen3.5-Flash for coding?

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Command A has none, so the two cannot be ranked on coding. Command A has the edge where the benchmark that matters is CaseLaw (Vals AI), where it leads.

Which is cheaper, Command A or Qwen3.5-Flash?

Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Per solved SWE-bench Verified task, Command A costs $2.69 and Qwen3.5-Flash $0.40.

Which has the bigger context window, Command A or Qwen3.5-Flash?

Qwen3.5-Flash, with 1M tokens against 256K.

How many benchmarks is the Command A vs Qwen3.5-Flash comparison based on?

41 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark 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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