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Command A vs Qwen3.8 Max (0902)

Qwen3.8 Max (0902) leads Command A on the Artificial Analysis Intelligence Index, 45.4 to 13.1, and Qwen3.8 Max (0902) costs 1.7x less per output token ($6.00 vs $10.00 per million). Updated October 21, 2026; 48 benchmarks have a result for both.

Command ACohere
Coding
No data
Overall
13.1
Output $/M
$10.00
0
Qwen3.8 Max (0902)Qwen
Coding
62.4
Overall
45.4
Output $/M
$6.00
48
vs boards won of 48 shared

Command A or Qwen3.8 Max (0902): which to pick

Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Command A has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
48
Command A only
12
Qwen3.8 Max (0902) only
65
Like-for-like categories
7 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 A not benchmarked, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
Widest category
Agentic work, 48.3 points apart on average over 2 shared benchmarks.
Widest single gap
SWE-bench Verified (Vals AI): Command A 7.8% against Qwen3.8 Max (0902) 85.6%, 77.8 points apart on a 0 to 100 scale.
Output price
Command A $10.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 1.7x apart.
Context window
Command A takes 256K tokens, Qwen3.8 Max (0902) 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 ABarsQwen3.8 Max (0902)Ties
Coding07
Intelligence01
Agentic work02
Reasoning06
Math02
Knowledge09
General021
All shared boards048
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
Coding benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
LiveBench codingNot measured60.3%Only Qwen3.8 Max (0902) measured
LMArena WebDevNot measured1674Only Qwen3.8 Max (0902) measured
AA Coding Index27.876.2Qwen3.8 Max (0902)
LiveCodeBench (Vals AI)35.1%87.8%Qwen3.8 Max (0902)
SWE-bench Verified (Vals AI)7.8%85.6%Qwen3.8 Max (0902)
Terminal-Bench 4 (Vals AI)Not measured34.3%Only Qwen3.8 Max (0902) measured
Vibe Code Bench (Vals AI)Not measured64.7%Only Qwen3.8 Max (0902) measured
Code migration (Vals AI)Not measured24.0%Only Qwen3.8 Max (0902) measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 Max (0902) measured
IOI (Vals AI)Not measured68.9%Only Qwen3.8 Max (0902) measured
Terminal-Bench 2.1 (Vals AI)17.6%67.4%Qwen3.8 Max (0902)
SWE-bench Multimodal (Vals AI)Not measured42.5%Only Qwen3.8 Max (0902) measured
Vibe Code Bench 1-100 (Vals AI)Not measured12.8%Only Qwen3.8 Max (0902) measured
SkillsBench (Vals AI)Not measured42.0%Only Qwen3.8 Max (0902) measured
CyberBench (Vals AI)Not measured28.6%Only Qwen3.8 Max (0902) measured
LiveCodeBench (Artificial Analysis run)28.7%Not measuredOnly Command A measured
SciCode38.5%53.2%Qwen3.8 Max (0902)
Terminal-Bench Hard (Artificial Analysis run)25.0%Not measuredOnly Command A measured
FrontierSWENot measured17.8%Only Qwen3.8 Max (0902) measured
LMArena Text: coding13301502Qwen3.8 Max (0902)
LMArena Text: software and IT13361498Qwen3.8 Max (0902)
LMArena WebDev: ReactNot measured1692Only Qwen3.8 Max (0902) measured
LMArena WebDev: HTMLNot measured1649Only Qwen3.8 Max (0902) measured
LMArena WebDev: from an imageNot measured1637Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
AA Intelligence Index13.145.4Qwen3.8 Max (0902)
Epoch Capabilities IndexNot measured157.4Only Qwen3.8 Max (0902) measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
AA Agentic Index1.056.0Qwen3.8 Max (0902)
Design Arena: agents building web appsNot measured1300Only Qwen3.8 Max (0902) measured
Design Arena: agents building full-stack appsNot measured1305Only Qwen3.8 Max (0902) measured
Design Arena: agents building mobile appsNot measured1224Only Qwen3.8 Max (0902) measured
Design Arena: agents building Android appsNot measured1202Only Qwen3.8 Max (0902) measured
Design Arena: agents building Godot gamesNot measured1234Only Qwen3.8 Max (0902) measured
Design Arena: PowerPoint slidesNot measured1258Only Qwen3.8 Max (0902) measured
Design Arena: spreadsheetsNot measured937Only Qwen3.8 Max (0902) measured
LiveBench researchNot measured69.9%Only Qwen3.8 Max (0902) measured
LiveBench browserNot measured32.0%Only Qwen3.8 Max (0902) measured
LiveBench long agenticNot measured42.3%Only Qwen3.8 Max (0902) measured
Finance Agent (Vals AI)9.0%50.6%Qwen3.8 Max (0902)
Tax Agent Bench (Vals AI)Not measured32.1%Only Qwen3.8 Max (0902) measured
Legal Research Bench (Vals AI)Not measured47.6%Only Qwen3.8 Max (0902) measured
Excel Modeling Benchmark (Vals AI)Not measured60.1%Only Qwen3.8 Max (0902) measured
Terminal-Bench-Science (Vals AI)Not measured12.9%Only Qwen3.8 Max (0902) measured
τ²-Bench Telecom80.7%Not measuredOnly Command A measured
APEX-AgentsNot measured63.3%Only Qwen3.8 Max (0902) measured
LMArena SearchNot measured1261Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
GPQA Diamond48.5%93.7%Qwen3.8 Max (0902)
LiveBench reasoningNot measured88.2%Only Qwen3.8 Max (0902) measured
MysteryMechanism (Vals AI)Not measured23.9%Only Qwen3.8 Max (0902) measured
MMMU Pro (Vals AI)Not measured88.0%Only Qwen3.8 Max (0902) measured
GPQA Diamond (Artificial Analysis run)76.1%92.8%Qwen3.8 Max (0902)
Humanity's Last Exam (Artificial Analysis run)12.0%43.1%Qwen3.8 Max (0902)
GPQA Diamond (Epoch AI run)Not measured92.7%Only Qwen3.8 Max (0902) measured
Chess puzzlesNot measured46.0%Only Qwen3.8 Max (0902) measured
Mystery game puzzlesNot measured38.0%Only Qwen3.8 Max (0902) measured
LMArena Text: hard prompts13261496Qwen3.8 Max (0902)
LMArena Text: expert12961507Qwen3.8 Max (0902)
LMArena Text: hard prompts in English13351503Qwen3.8 Max (0902)
LMArena Vision: diagramsNot measured1323Only Qwen3.8 Max (0902) measured
LMArena Vision: homeworkNot measured1336Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
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 measured100.0%Only Qwen3.8 Max (0902) measured
FrontierMath, tiers 1 to 3Not measured74.7%Only Qwen3.8 Max (0902) measured
FrontierMath, tier 4Not measured46.3%Only Qwen3.8 Max (0902) measured
ProofBenchNot measured58.0%Only Qwen3.8 Max (0902) measured
LMArena Text: math13001501Qwen3.8 Max (0902)
LMArena Text: mathematical work13121491Qwen3.8 Max (0902)
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index09
Knowledge benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
MMLU Pro69.2%88.6%Qwen3.8 Max (0902)
LegalBench (Vals AI)79.7%83.6%Qwen3.8 Max (0902)
CaseLaw (Vals AI)64.5%Not measuredOnly Command A measured
CorpFin (Vals AI)46.0%65.8%Qwen3.8 Max (0902)
TaxEval (Vals AI)61.4%75.5%Qwen3.8 Max (0902)
MortgageTax (Vals AI)Not measured64.0%Only Qwen3.8 Max (0902) measured
MedQA (Vals AI)80.5%Not measuredOnly Command A measured
MedCode (Vals AI)19.7%40.7%Qwen3.8 Max (0902)
MMLU Pro (Artificial Analysis run)71.2%Not measuredOnly Command A measured
SimpleQA VerifiedNot measured47.3%Only Qwen3.8 Max (0902) measured
LMArena Text: science13391512Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare13341503Qwen3.8 Max (0902)
LMArena Text: legal and government13481492Qwen3.8 Max (0902)
LMArena Text: business and finance13151480Qwen3.8 Max (0902)
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
Design Arena: websitesNot measured1275Only Qwen3.8 Max (0902) measured
Design Arena: UI componentsNot measured1340Only Qwen3.8 Max (0902) measured
Design Arena: game devNot measured1313Only Qwen3.8 Max (0902) measured
Design Arena: data vizNot measured1282Only Qwen3.8 Max (0902) measured
Design Arena: 3DNot measured1337Only Qwen3.8 Max (0902) measured
Design Arena: all code categoriesNot measured1293Only Qwen3.8 Max (0902) measured
Design Arena: ASCII artNot measured1200Only Qwen3.8 Max (0902) measured
LiveBench designNot measured78.6%Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
General benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
LiveBench data analysisNot measured78.4%Only Qwen3.8 Max (0902) measured
Public Benefits Bench (Vals AI)Not measured67.1%Only Qwen3.8 Max (0902) measured
SAGE (Vals AI)Not measured51.2%Only Qwen3.8 Max (0902) measured
MedScribe (Vals AI)55.7%85.0%Qwen3.8 Max (0902)
Vals Multimodal IndexNot measured65.4%Only Qwen3.8 Max (0902) measured
IFBench73.9%Not measuredOnly Command A measured
Long context reasoning (AA-LCR)52.7%80.3%Qwen3.8 Max (0902)
DTBench61.3%92.0%Qwen3.8 Max (0902)
LMCA10.3%46.2%Qwen3.8 Max (0902)
Furniture assemblyNot measured20.0%Only Qwen3.8 Max (0902) measured
LMArena Text13311483Qwen3.8 Max (0902)
LMArena Text: instruction following13091481Qwen3.8 Max (0902)
LMArena Text: creative writing13191477Qwen3.8 Max (0902)
LMArena VisionNot measured1313Only Qwen3.8 Max (0902) measured
LMArena Text: English13441491Qwen3.8 Max (0902)
LMArena Text: non-English13131473Qwen3.8 Max (0902)
LMArena Text: Chinese13271539Qwen3.8 Max (0902)
LMArena Text: German13421478Qwen3.8 Max (0902)
LMArena Text: Japanese12851473Qwen3.8 Max (0902)
LMArena Text: Korean12851460Qwen3.8 Max (0902)
LMArena Text: French13511498Qwen3.8 Max (0902)
LMArena Text: Spanish13471489Qwen3.8 Max (0902)
LMArena Text: Russian13141482Qwen3.8 Max (0902)
LMArena Text: Polish13241471Qwen3.8 Max (0902)
LMArena Text: multi-turn13381489Qwen3.8 Max (0902)
LMArena Text: longer queries13341488Qwen3.8 Max (0902)
LMArena Text: writing and language13281477Qwen3.8 Max (0902)
LMArena Text: entertainment and media13061464Qwen3.8 Max (0902)
LMArena Vision: EnglishNot measured1311Only Qwen3.8 Max (0902) measured
LMArena Vision: ChineseNot measured1358Only Qwen3.8 Max (0902) measured
LMArena Vision: reading textNot measured1322Only Qwen3.8 Max (0902) measured
LMArena Vision: humorNot measured1304Only Qwen3.8 Max (0902) measured
LMArena Vision: creative writingNot measured1312Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Command A and Qwen3.8 Max (0902)
BenchmarkCommand AQwen3.8 Max (0902)Leader
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
Qwen3.8 Max (0902)$0.0050Fits in one request

Qwen3.8 Max (0902) costs less

Repository review

50K input + 3K output tokens

Command A$0.155Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request

Qwen3.8 Max (0902) costs less

Agent loop

200K input + 10K output tokens

Command A$0.600Fits in one request
Qwen3.8 Max (0902)$0.460Fits in one request

Qwen3.8 Max (0902) 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 Qwen3.8 Max (0902)
SpecificationCohere Command AQwen3.8 Max (0902)
MakerCohereQwen
WeightsOpen weightsNo public weights listed
ReleasedMarch 13, 2025September 3, 2026
Context window256K1M
Input $/Mtok$2.50$2.00
Output $/Mtok$10.00$6.00
Coding indexNot benchmarked62.4
Independent measurements behind it15
Cost per solved task$2.69$1.32
SourceOpenRouter listingOpenRouter listing

Questions

Is Command A better than Qwen3.8 Max (0902) for coding?

Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Command A has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, Command A or Qwen3.8 Max (0902)?

Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, Command A costs $2.69 and Qwen3.8 Max (0902) $1.32.

Which has the bigger context window, Command A or Qwen3.8 Max (0902)?

Qwen3.8 Max (0902), with 1M tokens against 256K.

How many benchmarks is the Command A vs Qwen3.8 Max (0902) comparison based on?

48 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.

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