Enter opens the highlighted result. Esc closes.

Command A vs Qwen3 32B

Updated October 21, 2026. 37 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 32B
Command ACohere
Coding
No data
Overall
13.1
Output $/M
$10.00
17
Qwen3 32BQwen
Coding
No data
Overall
7.3
Output $/M
$0.40
20
vs boards won of 37 shared

Decision reading

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

Command A has the edge where the context window is larger, 256K against 131K tokens, and where what matters is LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model ACommand ACohereNot benchmarked1 independent benchmark$2.69 per solved taskModel BQwen3 32BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
37
Command A only
23
Qwen3 32B only
5
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 32B not benchmarked.
Widest category
Agentic work, 50.9 points apart on average over 1 shared benchmark.
Widest single gap
AA Math Index: Command A 13.0 against Qwen3 32B 73.0, 60.0 points apart on a 0 to 100 scale.
Output price
Command A $10.00 against Qwen3 32B $0.40 per million output tokens, 25.0x apart.
Context window
Command A takes 256K tokens, Qwen3 32B 131K.

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 32BTies
Coding23
Intelligence10
Agentic work10
Reasoning23
Math04
Knowledge14
General106
All shared boards1720
CodingLike-for-likeSix of these boards feed the Vibe Coding Index23
Coding benchmarks for Command A and Qwen3 32B
BenchmarkCommand AQwen3 32BLeader
Aider polyglotNot measured40.0%Only Qwen3 32B 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%54.6%Qwen3 32B
SciCode38.5%36.0%Command A
Terminal-Bench Hard (Artificial Analysis run)25.0%3.0%Command A
LMArena Text: coding13301357Qwen3 32B
LMArena Text: software and IT13361366Qwen3 32B
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Command A and Qwen3 32B
BenchmarkCommand AQwen3 32BLeader
AA Intelligence Index13.17.3Command A
Epoch Capabilities IndexNot measured138.4Only Qwen3 32B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Command A and Qwen3 32B
BenchmarkCommand AQwen3 32BLeader
AA Agentic Index1.0Not measuredOnly Command A measured
Finance Agent (Vals AI)9.0%Not measuredOnly Command A measured
τ²-Bench Telecom80.7%29.8%Command A
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
Reasoning benchmarks for Command A and Qwen3 32B
BenchmarkCommand AQwen3 32BLeader
GPQA Diamond48.5%Not measuredOnly Command A measured
GPQA Diamond (Artificial Analysis run)76.1%66.8%Command A
Humanity's Last Exam (Artificial Analysis run)12.0%7.4%Command A
GPQA Diamond (Epoch AI run)Not measured65.7%Only Qwen3 32B measured
LMArena Text: hard prompts13261334Qwen3 32B
LMArena Text: expert12961362Qwen3 32B
LMArena Text: hard prompts in English13351350Qwen3 32B
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Command A and Qwen3 32B
BenchmarkCommand AQwen3 32BLeader
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 Index13.073.0Qwen3 32B
AIME 2025 (Artificial Analysis run)13.0%73.0%Qwen3 32B
OTIS Mock AIMENot measured66.9%Only Qwen3 32B measured
LMArena Text: math13001399Qwen3 32B
LMArena Text: mathematical work13121420Qwen3 32B
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for Command A and Qwen3 32B
BenchmarkCommand AQwen3 32BLeader
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%79.8%Qwen3 32B
LMArena Text: science13391372Qwen3 32B
LMArena Text: medicine and healthcare13341368Qwen3 32B
LMArena Text: legal and government13481324Command A
LMArena Text: business and finance13151318Qwen3 32B
Neither model has a result on the other 5 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 32B
BenchmarkCommand AQwen3 32BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index106
General benchmarks for Command A and Qwen3 32B
BenchmarkCommand AQwen3 32BLeader
MedScribe (Vals AI)55.7%Not measuredOnly Command A measured
IFBench73.9%36.3%Command A
Long context reasoning (AA-LCR)52.7%0.0%Command A
DTBench61.3%67.5%Qwen3 32B
LMCA10.3%17.3%Qwen3 32B
Fiction.LiveBenchNot measured74.2%Only Qwen3 32B measured
LMArena Text13311340Qwen3 32B
LMArena Text: instruction following13091305Command A
LMArena Text: creative writing13191297Command A
LMArena Text: English13441359Qwen3 32B
LMArena Text: non-English13131317Qwen3 32B
LMArena Text: Chinese13271357Qwen3 32B
LMArena Text: German13421341Command A
LMArena Text: Japanese1285Not measuredOnly Command A measured
LMArena Text: Korean1285Not measuredOnly Command A measured
LMArena Text: French1351Not measuredOnly Command A measured
LMArena Text: Spanish1347Not measuredOnly Command A measured
LMArena Text: Russian13141311Command A
LMArena Text: Polish1324Not measuredOnly Command A measured
LMArena Text: multi-turn13381331Command A
LMArena Text: longer queries13341327Command A
LMArena Text: writing and language13281298Command A
LMArena Text: entertainment and media13061279Command A
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 32B
BenchmarkCommand AQwen3 32BLeader
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 32B$0.0003Fits in one request

Qwen3 32B costs less

Repository review

50K input + 3K output tokens

Command A$0.155Fits in one request
Qwen3 32B$0.0082Fits in one request

Qwen3 32B costs less

Agent loop

200K input + 10K output tokens

Command A$0.600Fits in one request
Qwen3 32B$0.032Exceeds the context window

Qwen3 32B 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 32B
SpecificationCohere Command AQwen3 32B
MakerCohereQwen
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025April 28, 2025
Context window256K131K
Input $/Mtok$2.50$0.14
Output $/Mtok$10.00$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved task$2.69Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command A better than Qwen3 32B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Command A has the edge where the context window is larger, 256K against 131K tokens, and where what matters is LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, Command A or Qwen3 32B?

Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen3 32B costs $0.14 and $0.40. Cost per solved task is known for Command A only.

Which has the bigger context window, Command A or Qwen3 32B?

Command A, with 256K tokens against 131K.

How many benchmarks is the Command A vs Qwen3 32B 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 32B's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next