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Command A vs Qwen3.5-35B-A3B

Qwen3.5-35B-A3B leads Command A on the Artificial Analysis Intelligence Index, 19.3 to 13.1, and Qwen3.5-35B-A3B costs 7.7x less per output token ($1.30 vs $10.00 per million). Updated October 21, 2026; 37 benchmarks have a result for both.

Replace Command A Replace Qwen3.5-35B-A3B
Command ACohere
Coding
No data
Overall
No data
Output $/M
$10.00
1
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
36
vs boards won of 37 shared

Command A or Qwen3.5-35B-A3B: which to pick

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

Pick Command A for work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model ACommand ACohereNot benchmarked1 independent benchmark$2.69 per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
37
Command A only
25
Qwen3.5-35B-A3B only
8
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, Qwen3.5-35B-A3B not benchmarked.
Widest category
Math, 16.8 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: Chinese: Command A 1327 against Qwen3.5-35B-A3B 1457, 21.5 points apart on a 0 to 100 scale.
Output price
Command A $10.00 against Qwen3.5-35B-A3B $1.30 per million output tokens, 7.7x apart.
Context window
Command A takes 256K tokens, Qwen3.5-35B-A3B 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 ABarsQwen3.5-35B-A3BTies
Coding03
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge04
General120
All shared boards136
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Command A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B 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%Not measuredOnly Command A measured
Terminal-Bench Hard (Artificial Analysis run)25.0%26.5%Qwen3.5-35B-A3B
ALE-BenchNot measured221.8Only Qwen3.5-35B-A3B measured
LMArena Text: coding13301410Qwen3.5-35B-A3B
LMArena Text: software and IT13361415Qwen3.5-35B-A3B
LMArena WebDev: ReactNot measured1238Only Qwen3.5-35B-A3B measured
LMArena WebDev: HTMLNot measured1301Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Command A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
AA Intelligence Index13.119.3Qwen3.5-35B-A3B
Epoch Capabilities IndexNot measured142.5Only Qwen3.5-35B-A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Command A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
AA Agentic Index1.0Not measuredOnly Command A measured
Finance Agent (Vals AI)9.0%Not measuredOnly Command A measured
τ²-Bench Telecom80.7%89.2%Qwen3.5-35B-A3B
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Berkeley Function Calling Leaderboard (BFCL)46.5%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 index05
Reasoning benchmarks for Command A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
GPQA Diamond48.5%Not measuredOnly Command A measured
GPQA Diamond (Artificial Analysis run)76.1%84.5%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)12.0%21.0%Qwen3.5-35B-A3B
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts13261400Qwen3.5-35B-A3B
LMArena Text: expert12961408Qwen3.5-35B-A3B
LMArena Text: hard prompts in English13351411Qwen3.5-35B-A3B
Kagi LLM Benchmark28.8%Not measuredOnly Command A 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 A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
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 measured70.0%Only Qwen3.5-35B-A3B measured
LMArena Text: math13001404Qwen3.5-35B-A3B
LMArena Text: mathematical work13121410Qwen3.5-35B-A3B
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Command A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
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: science13391413Qwen3.5-35B-A3B
LMArena Text: medicine and healthcare13341421Qwen3.5-35B-A3B
LMArena Text: legal and government13481399Qwen3.5-35B-A3B
LMArena Text: business and finance13151394Qwen3.5-35B-A3B
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 A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for Command A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
MedScribe (Vals AI)55.7%Not measuredOnly Command A measured
IFBench73.9%72.5%Command A
Long context reasoning (AA-LCR)52.7%72.0%Qwen3.5-35B-A3B
DTBench61.3%80.0%Qwen3.5-35B-A3B
LMCA10.3%29.5%Qwen3.5-35B-A3B
LMArena Text13311395Qwen3.5-35B-A3B
LMArena Text: instruction following13091379Qwen3.5-35B-A3B
LMArena Text: creative writing13191347Qwen3.5-35B-A3B
LMArena Text: English13441407Qwen3.5-35B-A3B
LMArena Text: non-English13131378Qwen3.5-35B-A3B
LMArena Text: Chinese13271457Qwen3.5-35B-A3B
LMArena Text: German13421367Qwen3.5-35B-A3B
LMArena Text: Japanese12851326Qwen3.5-35B-A3B
LMArena Text: Korean12851355Qwen3.5-35B-A3B
LMArena Text: French13511412Qwen3.5-35B-A3B
LMArena Text: Spanish13471390Qwen3.5-35B-A3B
LMArena Text: Russian13141376Qwen3.5-35B-A3B
LMArena Text: Polish13241385Qwen3.5-35B-A3B
LMArena Text: multi-turn13381390Qwen3.5-35B-A3B
LMArena Text: longer queries13341389Qwen3.5-35B-A3B
LMArena Text: writing and language13281365Qwen3.5-35B-A3B
LMArena Text: entertainment and media13061347Qwen3.5-35B-A3B
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Command A and Qwen3.5-35B-A3B
BenchmarkCommand AQwen3.5-35B-A3BLeader
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
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

Command A$0.155Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

Command A$0.600Fits in one request
Qwen3.5-35B-A3B$0.045Fits in one request

Qwen3.5-35B-A3B 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 Qwen3.5-35B-A3B
SpecificationCohere Command AQwen3.5-35B-A3B
MakerCohereQwen
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025February 25, 2026
Context window256K262K
Input $/Mtok$2.50$0.1625
Output $/Mtok$10.00$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it11
Cost per solved task$2.69Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command A better than Qwen3.5-35B-A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command A for work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, Command A or Qwen3.5-35B-A3B?

Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for Command A only.

Which has the bigger context window, Command A or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B, with 262K tokens against 256K.

How many benchmarks is the Command A vs Qwen3.5-35B-A3B comparison based on?

37 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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