Command A vs o3
Updated October 21, 2026. 53 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 200K tokens, and where what matters is LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 53
- Command A only
- 7
- o3 only
- 44
- 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
o3
o3 leads, 20.2 against 13.1.
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
o3
o3 leads, 84.1% against 48.5%.
Same board, both measured
Math
AIME
o3
o3 leads, 85.3% against 13.3%.
Same board, both measured
Knowledge
MMLU Pro
o3
o3 leads, 85.6% against 69.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only o3 has a Design Arena: websites result, 1036.
Directional only
Long documents
Listed context window
Command A
Command A takes 256K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
o3
Command A $0.0075, o3 $0.0060 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
o3
Command A $2.69, o3 $0.571.
Published attempt cost and pass rate
At a glance
- Coding index
- Command A not benchmarked, o3 not benchmarked.
- Widest category
- Math, 40.9 points apart on average over 7 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): Command A 13.0% against o3 88.3%, 75.3 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against o3 $8.00 per million output tokens, 1.3x apart.
- Context window
- Command A takes 256K tokens, o3 200K.
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 | o3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 0 | 1 tie | |
| Reasoning | 0 | 6 | ||
| Math | 0 | 7 | ||
| Knowledge | 0 | 11 | ||
| General | 1 | 21 | ||
| All shared boards | 1 | 51 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | Command A | o3 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 81.3% | Only o3 measured |
| SWE-bench Verified | Not measured | 58.4% | Only o3 measured |
| SWE-bench Multimodal | Not measured | 36.0% | Only o3 measured |
| AA Coding Index | 27.8 | Not measured | Only Command A measured |
| LiveCodeBench (Vals AI) | 35.1% | 83.9% | o3 |
| 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% | 80.8% | o3 |
| SciCode | 38.5% | Not measured | Only Command A measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 37.1% | o3 |
| GSO-Bench | Not measured | 8.8% | Only o3 measured |
| WeirdML | Not measured | 52.4% | Only o3 measured |
| ALE-Bench | Not measured | 933.5 | Only o3 measured |
| LMArena Text: coding | 1330 | 1407 | o3 |
| LMArena Text: software and IT | 1336 | 1415 | o3 |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Command A | o3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 20.2 | o3 |
| Epoch Capabilities Index | Not measured | 146.7 | Only o3 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index00
| Benchmark | Command A | o3 | 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% | 80.7% | Tie |
| METR time horizons | Not measured | 65.4% | Only o3 measured |
| GDPval | Not measured | 30.8% | Only o3 measured |
| DeepResearch Bench | Not measured | 45.2% | Only o3 measured |
| OSWorld | Not measured | 23.0% | Only o3 measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Command A | o3 | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | 84.1% | o3 |
| MMMU Pro (Vals AI) | Not measured | 80.4% | Only o3 measured |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 82.7% | o3 |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 20.1% | o3 |
| GPQA Diamond (Epoch AI run) | Not measured | 81.8% | Only o3 measured |
| ARC-AGI | Not measured | 60.8% | Only o3 measured |
| ARC-AGI-2 | Not measured | 6.5% | Only o3 measured |
| SimpleBench | Not measured | 53.1% | Only o3 measured |
| Chess puzzles | Not measured | 37.0% | Only o3 measured |
| Mystery game puzzles | Not measured | 29.0% | Only o3 measured |
| VPCT | Not measured | 52.0% | Only o3 measured |
| LMArena Text: hard prompts | 1326 | 1402 | o3 |
| LMArena Text: expert | 1296 | 1402 | o3 |
| LMArena Text: hard prompts in English | 1335 | 1411 | o3 |
| LMArena Vision: diagrams | Not measured | 1220 | Only o3 measured |
| LMArena Vision: homework | Not measured | 1234 | Only o3 measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Command A | o3 | Leader |
|---|---|---|---|
| AIME | 13.3% | 85.3% | o3 |
| MATH 500 (Vals AI) | 76.2% | 94.6% | o3 |
| MGSM (Vals AI) | 85.7% | 91.8% | o3 |
| AA Math Index | 13.0 | 88.3 | o3 |
| AIME 2025 (Artificial Analysis run) | 13.0% | 88.3% | o3 |
| OTIS Mock AIME | Not measured | 84.4% | Only o3 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 33.3% | Only o3 measured |
| MATH level 5 | Not measured | 97.8% | Only o3 measured |
| LMArena Text: math | 1300 | 1426 | o3 |
| LMArena Text: mathematical work | 1312 | 1423 | o3 |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index011
| Benchmark | Command A | o3 | Leader |
|---|---|---|---|
| MMLU Pro | 69.2% | 85.6% | o3 |
| LegalBench (Vals AI) | 79.7% | 83.8% | o3 |
| CaseLaw (Vals AI) | 64.5% | Not measured | Only Command A measured |
| CorpFin (Vals AI) | 46.0% | 59.7% | o3 |
| TaxEval (Vals AI) | 61.4% | 74.6% | o3 |
| MortgageTax (Vals AI) | Not measured | 65.7% | Only o3 measured |
| MedQA (Vals AI) | 80.5% | 96.1% | o3 |
| MedCode (Vals AI) | 19.7% | 47.3% | o3 |
| MMLU Pro (Artificial Analysis run) | 71.2% | 85.3% | o3 |
| SimpleQA Verified | Not measured | 49.4% | Only o3 measured |
| GeoBench | Not measured | 74.0% | Only o3 measured |
| LMArena Text: science | 1339 | 1429 | o3 |
| LMArena Text: medicine and healthcare | 1334 | 1448 | o3 |
| LMArena Text: legal and government | 1348 | 1428 | o3 |
| LMArena Text: business and finance | 1315 | 1393 | o3 |
| Neither model has a result on the other 2 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Command A | o3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1036 | Only o3 measured |
| Design Arena: UI components | Not measured | 1017 | Only o3 measured |
| Design Arena: game dev | Not measured | 1034 | Only o3 measured |
| Design Arena: data viz | Not measured | 1200 | Only o3 measured |
| Design Arena: all code categories | Not measured | 1020 | Only o3 measured |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index121
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | o3 | 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
o3 costs less
Repository review
50K input + 3K output tokens
o3 costs less
Agent loop
200K input + 10K output tokens
o3 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 | OpenAI o3 |
|---|---|---|
| Maker | Cohere | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | March 13, 2025 | April 16, 2025 |
| Context window | 256K | 200K |
| Input $/Mtok | $2.50 | $2.00 |
| Output $/Mtok | $10.00 | $8.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $2.69 | $0.571 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Command A better than o3 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 200K tokens, and where what matters is LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, Command A or o3?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; o3 costs $2.00 and $8.00. Per solved SWE-bench Verified task, Command A costs $2.69 and o3 $0.571.
Which has the bigger context window, Command A or o3?
Command A, with 256K tokens against 200K.
How many benchmarks is the Command A vs o3 comparison based on?
53 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and o3's on 0. Where only one model has a result, the page says so instead of naming a winner.