Command A vs Qwen-Plus
Updated October 21, 2026. 25 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
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 LMArena Text: software and IT or LMArena Text: expert, where it leads.
- Shared results
- 25
- Command A only
- 35
- Qwen-Plus only
- 3
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Command A has a AA Intelligence Index result, 13.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Command A has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Command A has a GPQA Diamond result, 48.5%.
Directional only
Math
AIME
No call
Only Command A has a AIME result, 13.3%.
Directional only
Knowledge
MMLU Pro
No call
Only Command A has a MMLU Pro result, 69.2%.
Directional only
Long documents
Listed context window
Qwen-Plus
Qwen-Plus takes 1M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen-Plus
Command A $0.0075, Qwen-Plus $0.0006 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Command A has the number, $2.69.
Directional only
At a glance
- Coding index
- Command A not benchmarked, Qwen-Plus not benchmarked.
- Widest category
- General, 4.6 points apart on average over 14 shared benchmarks.
- Widest single gap
- DTBench: Command A 61.3% against Qwen-Plus 81.1%, 19.7 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against Qwen-Plus $0.78 per million output tokens, 12.8x apart.
- Context window
- Command A takes 256K tokens, Qwen-Plus 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.
| Category | Command A | Bars | Qwen-Plus | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Reasoning | 2 | 1 | ||
| Math | 0 | 2 | ||
| Knowledge | 1 | 3 | ||
| General | 10 | 4 | ||
| All shared boards | 14 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| AA Coding Index | 27.8 | Not measured | Only Command A measured |
| LiveCodeBench (Vals AI) | 35.1% | Not measured | Only Command A measured |
| SWE-bench Verified (Vals AI) | 7.8% | Not measured | Only Command A measured |
| Terminal-Bench 2.1 (Vals AI) | 17.6% | Not measured | Only Command A measured |
| LiveCodeBench (Artificial Analysis run) | 28.7% | Not measured | Only Command A measured |
| SciCode | 38.5% | Not measured | Only Command A measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | Not measured | Only Command A measured |
| LMArena Text: coding | 1330 | 1328 | Command A |
| LMArena Text: software and IT | 1336 | 1343 | Qwen-Plus |
| Neither model has a result on the other 29 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | Not measured | Only Command A measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Command A measured |
| Finance Agent (Vals AI) | 9.0% | Not measured | Only Command A measured |
| τ²-Bench Telecom | 80.7% | Not measured | Only 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 index21
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | Not measured | Only Command A measured |
| GPQA Diamond (Artificial Analysis run) | 76.1% | Not measured | Only Command A measured |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | Not measured | Only Command A measured |
| GPQA Diamond (Epoch AI run) | Not measured | 48.1% | Only Qwen-Plus measured |
| LMArena Text: hard prompts | 1326 | 1317 | Command A |
| LMArena Text: expert | 1296 | 1328 | Qwen-Plus |
| LMArena Text: hard prompts in English | 1335 | 1333 | Command A |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| AIME | 13.3% | Not measured | Only Command A measured |
| MATH 500 (Vals AI) | 76.2% | Not measured | Only Command A measured |
| MGSM (Vals AI) | 85.7% | Not measured | Only Command A measured |
| AA Math Index | 13.0 | Not measured | Only Command A measured |
| AIME 2025 (Artificial Analysis run) | 13.0% | Not measured | Only Command A measured |
| OTIS Mock AIME | Not measured | 17.8% | Only Qwen-Plus measured |
| MATH level 5 | Not measured | 65.3% | Only Qwen-Plus measured |
| LMArena Text: math | 1300 | 1326 | Qwen-Plus |
| LMArena Text: mathematical work | 1312 | 1332 | Qwen-Plus |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| MMLU Pro | 69.2% | Not measured | Only Command A measured |
| LegalBench (Vals AI) | 79.7% | Not measured | Only Command A measured |
| CaseLaw (Vals AI) | 64.5% | Not measured | Only Command A measured |
| CorpFin (Vals AI) | 46.0% | Not measured | Only Command A measured |
| TaxEval (Vals AI) | 61.4% | Not measured | Only Command A measured |
| MedQA (Vals AI) | 80.5% | Not measured | Only Command A measured |
| MedCode (Vals AI) | 19.7% | Not measured | Only Command A measured |
| MMLU Pro (Artificial Analysis run) | 71.2% | Not measured | Only Command A measured |
| LMArena Text: science | 1339 | 1352 | Qwen-Plus |
| LMArena Text: medicine and healthcare | 1334 | 1350 | Qwen-Plus |
| LMArena Text: legal and government | 1348 | 1349 | Qwen-Plus |
| LMArena Text: business and finance | 1315 | 1303 | Command A |
| 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
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index104
| Benchmark | Command A | Qwen-Plus | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | Not measured | Only Command A measured |
| IFBench | 73.9% | Not measured | Only Command A measured |
| Long context reasoning (AA-LCR) | 52.7% | Not measured | Only Command A measured |
| DTBench | 61.3% | 81.1% | Qwen-Plus |
| LMCA | 10.3% | 24.0% | Qwen-Plus |
| LMArena Text | 1331 | 1326 | Command A |
| LMArena Text: instruction following | 1309 | 1303 | Command A |
| LMArena Text: creative writing | 1319 | 1292 | Command A |
| LMArena Text: English | 1344 | 1339 | Command A |
| LMArena Text: non-English | 1313 | 1310 | Command A |
| LMArena Text: Chinese | 1327 | 1347 | Qwen-Plus |
| LMArena Text: German | 1342 | Not measured | Only Command A measured |
| LMArena Text: Japanese | 1285 | 1251 | Command A |
| LMArena Text: Korean | 1285 | Not measured | Only Command A measured |
| LMArena Text: French | 1351 | Not measured | Only Command A measured |
| LMArena Text: Spanish | 1347 | Not measured | Only Command A measured |
| LMArena Text: Russian | 1314 | 1323 | Qwen-Plus |
| LMArena Text: Polish | 1324 | Not measured | Only Command A measured |
| LMArena Text: multi-turn | 1338 | 1336 | Command A |
| LMArena Text: longer queries | 1334 | 1324 | Command A |
| LMArena Text: writing and language | 1328 | 1296 | Command A |
| LMArena Text: entertainment and media | 1306 | 1270 | Command A |
| 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
| Benchmark | Command A | Qwen-Plus | 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
Qwen-Plus costs less
Repository review
50K input + 3K output tokens
Qwen-Plus costs less
Agent loop
200K input + 10K output tokens
Qwen-Plus 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.
| Specification | Cohere Command A | Qwen-Plus |
|---|---|---|
| Maker | Cohere | Qwen |
| Weights | Open weights | No public weights listed |
| Released | March 13, 2025 | February 1, 2025 |
| Context window | 256K | 1M |
| Input $/Mtok | $2.50 | $0.26 |
| Output $/Mtok | $10.00 | $0.78 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $2.69 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Command A better than Qwen-Plus 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 LMArena Text: software and IT or LMArena Text: expert, where it leads.
Which is cheaper, Command A or Qwen-Plus?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen-Plus costs $0.26 and $0.78. Cost per solved task is known for Command A only.
Which has the bigger context window, Command A or Qwen-Plus?
Qwen-Plus, with 1M tokens against 256K.
How many benchmarks is the Command A vs Qwen-Plus comparison based on?
25 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and Qwen-Plus's on 0. Where only one model has a result, the page says so instead of naming a winner.