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Command A vs Qwen3.5 397B A17B

Updated October 21, 2026. 38 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 397B A17B
Command ACohere
Coding
No data
Overall
13.1
Output $/M
$10.00
0
Qwen3.5 397B A17BQwen
Coding
No data
Overall
21.4
Output $/M
$2.34
38
vs boards won of 38 shared

Decision reading

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

Command A has the edge where what matters is SciCode or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model ACommand ACohereNot benchmarked1 independent benchmark$2.69 per solved taskModel BQwen3.5 397B A17BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
38
Command A only
22
Qwen3.5 397B A17B only
27
Like-for-like categories
7 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 397B A17B not benchmarked.
Widest category
Math, 24.6 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: Chinese: Command A 1327 against Qwen3.5 397B A17B 1498, 28.5 points apart on a 0 to 100 scale.
Output price
Command A $10.00 against Qwen3.5 397B A17B $2.34 per million output tokens, 4.3x apart.
Context window
Command A takes 256K tokens, Qwen3.5 397B A17B 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 ABarsQwen3.5 397B A17BTies
Coding04
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge04
General021
All shared boards038
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Command A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
LMArena WebDevNot measured1400Only Qwen3.5 397B A17B measured
AA Coding Index27.8Not measuredOnly Command A measured
LiveCodeBench (Vals AI)35.1%Not measuredOnly Command A measured
SWE-bench Verified (Vals AI)7.8%Not measuredOnly Command A measured
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%44.8%Qwen3.5 397B A17B
Terminal-Bench Hard (Artificial Analysis run)25.0%40.9%Qwen3.5 397B A17B
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: coding13301464Qwen3.5 397B A17B
LMArena Text: software and IT13361463Qwen3.5 397B A17B
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTMLNot measured1410Only Qwen3.5 397B A17B measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Command A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
AA Intelligence Index13.121.4Qwen3.5 397B A17B
Epoch Capabilities IndexNot measured146.8Only Qwen3.5 397B A17B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Command A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
AA Agentic Index1.0Not measuredOnly Command A measured
Finance Agent (Vals AI)9.0%Not measuredOnly Command A measured
τ²-Bench Telecom80.7%95.6%Qwen3.5 397B A17B
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Command A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
GPQA Diamond48.5%Not measuredOnly Command A measured
GPQA Diamond (Artificial Analysis run)76.1%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)12.0%29.0%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)Not measured86.4%Only Qwen3.5 397B A17B measured
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts13261448Qwen3.5 397B A17B
LMArena Text: expert12961462Qwen3.5 397B A17B
LMArena Text: hard prompts in English13351450Qwen3.5 397B A17B
LMArena Vision: diagramsNot measured1277Only Qwen3.5 397B A17B measured
LMArena Vision: homeworkNot measured1292Only Qwen3.5 397B A17B measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Command A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
AIME13.3%Not measuredOnly Command A measured
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 measured88.9%Only Qwen3.5 397B A17B measured
FrontierMath, tiers 1 to 3Not measured31.2%Only Qwen3.5 397B A17B measured
LMArena Text: math13001453Qwen3.5 397B A17B
LMArena Text: mathematical work13121454Qwen3.5 397B A17B
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 A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
MMLU Pro69.2%Not measuredOnly Command A measured
LegalBench (Vals AI)79.7%Not measuredOnly Command A measured
CaseLaw (Vals AI)64.5%Not measuredOnly Command A measured
CorpFin (Vals AI)46.0%Not measuredOnly Command A measured
TaxEval (Vals AI)61.4%Not measuredOnly Command A measured
MedQA (Vals AI)80.5%Not measuredOnly Command A measured
MedCode (Vals AI)19.7%Not measuredOnly Command A measured
MMLU Pro (Artificial Analysis run)71.2%Not measuredOnly Command A measured
LMArena Text: science13391457Qwen3.5 397B A17B
LMArena Text: medicine and healthcare13341455Qwen3.5 397B A17B
LMArena Text: legal and government13481441Qwen3.5 397B A17B
LMArena Text: business and finance13151435Qwen3.5 397B A17B
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Command A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
Design Arena: websitesNot measured1191Only Qwen3.5 397B A17B measured
Design Arena: UI componentsNot measured1163Only Qwen3.5 397B A17B measured
Design Arena: game devNot measured1140Only Qwen3.5 397B A17B measured
Design Arena: data vizNot measured1175Only Qwen3.5 397B A17B measured
Design Arena: 3DNot measured1161Only Qwen3.5 397B A17B measured
Design Arena: all code categoriesNot measured1180Only Qwen3.5 397B A17B measured
Design Arena: SVGNot measured1140Only Qwen3.5 397B A17B measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
General benchmarks for Command A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
MedScribe (Vals AI)55.7%Not measuredOnly Command A measured
IFBench73.9%78.8%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)52.7%77.3%Qwen3.5 397B A17B
DTBench61.3%87.5%Qwen3.5 397B A17B
LMCA10.3%37.9%Qwen3.5 397B A17B
LMArena Text13311437Qwen3.5 397B A17B
LMArena Text: instruction following13091424Qwen3.5 397B A17B
LMArena Text: creative writing13191402Qwen3.5 397B A17B
LMArena VisionNot measured1262Only Qwen3.5 397B A17B measured
LMArena Text: English13441443Qwen3.5 397B A17B
LMArena Text: non-English13131430Qwen3.5 397B A17B
LMArena Text: Chinese13271498Qwen3.5 397B A17B
LMArena Text: German13421445Qwen3.5 397B A17B
LMArena Text: Japanese12851429Qwen3.5 397B A17B
LMArena Text: Korean12851384Qwen3.5 397B A17B
LMArena Text: French13511462Qwen3.5 397B A17B
LMArena Text: Spanish13471441Qwen3.5 397B A17B
LMArena Text: Russian13141430Qwen3.5 397B A17B
LMArena Text: Polish13241447Qwen3.5 397B A17B
LMArena Text: multi-turn13381446Qwen3.5 397B A17B
LMArena Text: longer queries13341441Qwen3.5 397B A17B
LMArena Text: writing and language13281415Qwen3.5 397B A17B
LMArena Text: entertainment and media13061399Qwen3.5 397B A17B
LMArena Vision: EnglishNot measured1268Only Qwen3.5 397B A17B measured
LMArena Vision: ChineseNot measured1314Only Qwen3.5 397B A17B measured
LMArena Vision: reading textNot measured1271Only Qwen3.5 397B A17B measured
LMArena Vision: humorNot measured1262Only Qwen3.5 397B A17B measured
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writingNot measured1260Only Qwen3.5 397B A17B 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 A and Qwen3.5 397B A17B
BenchmarkCommand AQwen3.5 397B A17BLeader
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 397B A17B$0.0016Fits in one request

Qwen3.5 397B A17B costs less

Repository review

50K input + 3K output tokens

Command A$0.155Fits in one request
Qwen3.5 397B A17B$0.027Fits in one request

Qwen3.5 397B A17B costs less

Agent loop

200K input + 10K output tokens

Command A$0.600Fits in one request
Qwen3.5 397B A17B$0.101Fits in one request

Qwen3.5 397B A17B 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 397B A17B
SpecificationCohere Command AQwen3.5 397B A17B
MakerCohereQwen
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025February 16, 2026
Context window256K262K
Input $/Mtok$2.50$0.39
Output $/Mtok$10.00$2.34
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it11
Cost per solved task$2.69Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command A better than Qwen3.5 397B A17B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Command A has the edge where what matters is SciCode or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, Command A or Qwen3.5 397B A17B?

Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for Command A only.

Which has the bigger context window, Command A or Qwen3.5 397B A17B?

Qwen3.5 397B A17B, with 262K tokens against 256K.

How many benchmarks is the Command A vs Qwen3.5 397B A17B comparison based on?

38 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 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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