Command A vs Qwen2.5 72B Instruct
Updated October 21, 2026. 39 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 the context window is larger, 256K against 33K tokens, and where what matters is AA Math Index or AIME 2025 (Artificial Analysis run), where it leads.
- Shared results
- 39
- Command A only
- 21
- Qwen2.5 72B Instruct only
- 14
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Command A
Command A leads, 13.1 against 7.7.
Same board, both measured
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
Command A
Command A takes 256K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 72B Instruct
Command A $0.0075, Qwen2.5 72B Instruct $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, Qwen2.5 72B Instruct not benchmarked.
- Widest category
- Agentic work, 46.2 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Command A 80.7% against Qwen2.5 72B Instruct 34.5%, 46.2 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against Qwen2.5 72B Instruct $0.40 per million output tokens, 25.0x apart.
- Context window
- Command A takes 256K tokens, Qwen2.5 72B Instruct 33K.
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 | Qwen2.5 72B Instruct | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 2 | ||
| Knowledge | 4 | 1 | ||
| General | 17 | 2 | ||
| All shared boards | 34 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | Command A | Qwen2.5 72B Instruct | 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% | 27.6% | Command A |
| SciCode | 38.5% | Not measured | Only Command A measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 4.5% | Command A |
| WeirdML | Not measured | 16.0% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: coding | 1330 | 1292 | Command A |
| LMArena Text: software and IT | 1336 | 1292 | Command A |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Command A | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 7.7 | Command A |
| Epoch Capabilities Index | Not measured | 129.0 | Only Qwen2.5 72B Instruct measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Command A | Qwen2.5 72B Instruct | 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% | 34.5% | Command A |
| METR time horizons | Not measured | 35.8% | Only Qwen2.5 72B Instruct measured |
| BALROG | Not measured | 16.2% | Only Qwen2.5 72B Instruct measured |
| TheAgentCompany | Not measured | 5.7% | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Command A | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | Not measured | Only Command A measured |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 49.1% | Command A |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 3.6% | Command A |
| GPQA Diamond (Epoch AI run) | Not measured | 49.1% | Only Qwen2.5 72B Instruct measured |
| BIG-Bench Hard | Not measured | 79.8% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | 1326 | 1271 | Command A |
| LMArena Text: expert | 1296 | 1245 | Command A |
| LMArena Text: hard prompts in English | 1335 | 1279 | Command A |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Command A | Qwen2.5 72B Instruct | 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 | 14.0 | Qwen2.5 72B Instruct |
| AIME 2025 (Artificial Analysis run) | 13.0% | 14.0% | Qwen2.5 72B Instruct |
| OTIS Mock AIME | Not measured | 8.1% | Only Qwen2.5 72B Instruct measured |
| MATH level 5 | Not measured | 63.2% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: math | 1300 | 1283 | Command A |
| LMArena Text: mathematical work | 1312 | 1290 | Command A |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Command A | Qwen2.5 72B Instruct | 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% | 72.0% | Qwen2.5 72B Instruct |
| MMLU | Not measured | 85.3% | Only Qwen2.5 72B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 94.5% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: science | 1339 | 1275 | Command A |
| LMArena Text: medicine and healthcare | 1334 | 1258 | Command A |
| LMArena Text: legal and government | 1348 | 1288 | Command A |
| LMArena Text: business and finance | 1315 | 1253 | Command A |
| Neither model has a result on the other 3 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index172
| Benchmark | Command A | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | Not measured | Only Command A measured |
| IFBench | 73.9% | 36.9% | Command A |
| Long context reasoning (AA-LCR) | 52.7% | Not measured | Only Command A measured |
| DTBench | 61.3% | 62.9% | Qwen2.5 72B Instruct |
| LMCA | 10.3% | 13.4% | Qwen2.5 72B Instruct |
| HellaSwag | Not measured | 84.8% | Only Qwen2.5 72B Instruct measured |
| WinoGrande | Not measured | 82.3% | Only Qwen2.5 72B Instruct measured |
| PIQA | Not measured | 82.6% | Only Qwen2.5 72B Instruct measured |
| LMArena Text | 1331 | 1269 | Command A |
| LMArena Text: instruction following | 1309 | 1254 | Command A |
| LMArena Text: creative writing | 1319 | 1221 | Command A |
| LMArena Text: English | 1344 | 1283 | Command A |
| LMArena Text: non-English | 1313 | 1252 | Command A |
| LMArena Text: Chinese | 1327 | 1273 | Command A |
| LMArena Text: German | 1342 | 1234 | Command A |
| LMArena Text: Japanese | 1285 | 1180 | Command A |
| LMArena Text: Korean | 1285 | 1188 | Command A |
| LMArena Text: French | 1351 | 1280 | Command A |
| LMArena Text: Spanish | 1347 | 1255 | Command A |
| LMArena Text: Russian | 1314 | 1264 | Command A |
| LMArena Text: Polish | 1324 | Not measured | Only Command A measured |
| LMArena Text: multi-turn | 1338 | 1272 | Command A |
| LMArena Text: longer queries | 1334 | 1281 | Command A |
| LMArena Text: writing and language | 1328 | 1247 | Command A |
| LMArena Text: entertainment and media | 1306 | 1211 | Command A |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | Qwen2.5 72B Instruct | 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
Qwen2.5 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 72B Instruct 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 | Qwen2.5 72B Instruct |
|---|---|---|
| Maker | Cohere | Qwen |
| Weights | Open weights | Open weights |
| Released | March 13, 2025 | September 19, 2024 |
| Context window | 256K | 33K |
| Input $/Mtok | $2.50 | $0.36 |
| Output $/Mtok | $10.00 | $0.40 |
| 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 Qwen2.5 72B Instruct 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 33K tokens, and where what matters is AA Math Index or AIME 2025 (Artificial Analysis run), where it leads.
Which is cheaper, Command A or Qwen2.5 72B Instruct?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen2.5 72B Instruct costs $0.36 and $0.40. Cost per solved task is known for Command A only.
Which has the bigger context window, Command A or Qwen2.5 72B Instruct?
Command A, with 256K tokens against 33K.
How many benchmarks is the Command A vs Qwen2.5 72B Instruct comparison based on?
39 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and Qwen2.5 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.