Command A vs GPT-4o (2024-08-06)
Updated October 21, 2026. 43 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 128K tokens, and where what matters is LiveCodeBench (Artificial Analysis run) or AIME, where it leads.
- Shared results
- 43
- Command A only
- 17
- GPT-4o (2024-08-06) only
- 15
- 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
GPT-4o (2024-08-06)
GPT-4o (2024-08-06) leads, 14.0% against 13.3%.
Same board, both measured
Knowledge
MMLU Pro
GPT-4o (2024-08-06)
GPT-4o (2024-08-06) leads, 74.1% against 69.2%.
Same board, both measured
Long documents
Listed context window
Command A
Command A takes 256K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
Command A $0.0075, GPT-4o (2024-08-06) $0.0075 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, GPT-4o (2024-08-06) not benchmarked.
- Widest category
- Agentic work, 51.8 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Command A 80.7% against GPT-4o (2024-08-06) 28.9%, 51.8 points apart on a 0 to 100 scale.
- Output price
- Both cost $10.00 per million output tokens.
- Context window
- Command A takes 256K tokens, GPT-4o (2024-08-06) 128K.
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 | GPT-4o (2024-08-06) | Ties |
|---|---|---|---|---|
| Coding | 3 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 3 | 2 | ||
| Knowledge | 5 | 4 | ||
| General | 18 | 0 | ||
| All shared boards | 36 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
| Benchmark | Command A | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 23.1% | Only GPT-4o (2024-08-06) measured |
| SWE-bench Lite | Not measured | 21.7% | Only GPT-4o (2024-08-06) measured |
| 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% | 31.7% | GPT-4o (2024-08-06) |
| SciCode | 38.5% | Not measured | Only Command A measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 8.3% | Command A |
| LMArena Text: coding | 1330 | 1283 | Command A |
| LMArena Text: software and IT | 1336 | 1278 | Command A |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Command A | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 7.7 | Command A |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Command A | GPT-4o (2024-08-06) | 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% | 28.9% | Command A |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Command A | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | Not measured | Only Command A measured |
| MMMU Pro (Vals AI) | Not measured | 64.0% | Only GPT-4o (2024-08-06) measured |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 52.1% | Command A |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 2.3% | Command A |
| GPQA Diamond (Epoch AI run) | Not measured | 49.2% | Only GPT-4o (2024-08-06) measured |
| SimpleBench | Not measured | 17.8% | Only GPT-4o (2024-08-06) measured |
| Chess puzzles | Not measured | 6.0% | Only GPT-4o (2024-08-06) measured |
| LMArena Text: hard prompts | 1326 | 1264 | Command A |
| LMArena Text: expert | 1296 | 1241 | Command A |
| LMArena Text: hard prompts in English | 1335 | 1277 | Command A |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | Command A | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| AIME | 13.3% | 14.0% | GPT-4o (2024-08-06) |
| MATH 500 (Vals AI) | 76.2% | 75.2% | Command A |
| MGSM (Vals AI) | 85.7% | 90.7% | GPT-4o (2024-08-06) |
| 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 | 6.4% | Only GPT-4o (2024-08-06) measured |
| FrontierMath, tiers 1 to 3 | Not measured | 0.4% | Only GPT-4o (2024-08-06) measured |
| MATH level 5 | Not measured | 53.3% | Only GPT-4o (2024-08-06) measured |
| LMArena Text: math | 1300 | 1285 | Command A |
| LMArena Text: mathematical work | 1312 | 1283 | Command A |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index54
| Benchmark | Command A | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| MMLU Pro | 69.2% | 74.1% | GPT-4o (2024-08-06) |
| LegalBench (Vals AI) | 79.7% | 80.1% | GPT-4o (2024-08-06) |
| CaseLaw (Vals AI) | 64.5% | Not measured | Only Command A measured |
| CorpFin (Vals AI) | 46.0% | 39.4% | Command A |
| TaxEval (Vals AI) | 61.4% | 71.1% | GPT-4o (2024-08-06) |
| MortgageTax (Vals AI) | Not measured | 61.0% | Only GPT-4o (2024-08-06) measured |
| MedQA (Vals AI) | 80.5% | 88.2% | GPT-4o (2024-08-06) |
| MedCode (Vals AI) | 19.7% | Not measured | Only Command A measured |
| MMLU Pro (Artificial Analysis run) | 71.2% | Not measured | Only Command A measured |
| SimpleQA Verified | Not measured | 26.0% | Only GPT-4o (2024-08-06) measured |
| MMLU | Not measured | 84.3% | Only GPT-4o (2024-08-06) measured |
| LMArena Text: science | 1339 | 1274 | Command A |
| LMArena Text: medicine and healthcare | 1334 | 1252 | Command A |
| LMArena Text: legal and government | 1348 | 1275 | Command A |
| LMArena Text: business and finance | 1315 | 1232 | Command A |
| Neither model has a result on the other 2 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | Command A | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | Not measured | Only Command A measured |
| IFBench | 73.9% | 36.0% | Command A |
| Long context reasoning (AA-LCR) | 52.7% | 41.0% | Command A |
| DTBench | 61.3% | Not measured | Only Command A measured |
| LMCA | 10.3% | Not measured | Only Command A measured |
| LMArena Text | 1331 | 1283 | Command A |
| LMArena Text: instruction following | 1309 | 1267 | Command A |
| LMArena Text: creative writing | 1319 | 1274 | Command A |
| LMArena Vision | Not measured | 1065 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: English | 1344 | 1297 | Command A |
| LMArena Text: non-English | 1313 | 1262 | Command A |
| LMArena Text: Chinese | 1327 | 1254 | Command A |
| LMArena Text: German | 1342 | 1257 | Command A |
| LMArena Text: Japanese | 1285 | 1234 | Command A |
| LMArena Text: Korean | 1285 | 1218 | Command A |
| LMArena Text: French | 1351 | 1263 | Command A |
| LMArena Text: Spanish | 1347 | 1269 | Command A |
| LMArena Text: Russian | 1314 | 1272 | Command A |
| LMArena Text: Polish | 1324 | Not measured | Only Command A measured |
| LMArena Text: multi-turn | 1338 | 1279 | Command A |
| LMArena Text: longer queries | 1334 | 1283 | Command A |
| LMArena Text: writing and language | 1328 | 1290 | Command A |
| LMArena Text: entertainment and media | 1306 | 1267 | Command A |
| LMArena Vision: English | Not measured | 1072 | Only GPT-4o (2024-08-06) measured |
| LMArena Vision: Chinese | Not measured | 1009 | Only GPT-4o (2024-08-06) measured |
| 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 | GPT-4o (2024-08-06) | 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
Same cost
Repository review
50K input + 3K output tokens
Same cost
Agent loop
200K input + 10K output tokens
Same cost
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 GPT-4o (2024-08-06) |
|---|---|---|
| Maker | Cohere | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | March 13, 2025 | August 6, 2024 |
| Context window | 256K | 128K |
| Input $/Mtok | $2.50 | $2.50 |
| Output $/Mtok | $10.00 | $10.00 |
| 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 GPT-4o (2024-08-06) 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 128K tokens, and where what matters is LiveCodeBench (Artificial Analysis run) or AIME, where it leads.
Which is cheaper, Command A or GPT-4o (2024-08-06)?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; GPT-4o (2024-08-06) costs $2.50 and $10.00. Cost per solved task is known for Command A only.
Which has the bigger context window, Command A or GPT-4o (2024-08-06)?
Command A, with 256K tokens against 128K.
How many benchmarks is the Command A vs GPT-4o (2024-08-06) comparison based on?
43 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and GPT-4o (2024-08-06)'s on 0. Where only one model has a result, the page says so instead of naming a winner.