Model comparison
Command A vs gpt-oss-120b
Command A and gpt-oss-120b score almost the same on the Noometry Index (36.5 vs 36.3), so choose on price, context window or the category you care about most.
Last verified . 23 shared benchmarks.
CohereSummary
- They share 23 benchmarks with published results for both. Command A scores higher in 3 categories and gpt-oss-120b in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Command A leads 35.9 to 12.2.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for Command A and 58.6% for gpt-oss-120b.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $2.50 / $10 for Command A.
- Command A accepts more context: 256K tokens versus 131K.
Side by side
| Command A | gpt-oss-120b | |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 36.5 | 36.3 |
| Released | 2025-03-13 | 2025-08-05 |
| Weights | Open | Open |
| Context window | 256K | 131K |
| Max output | 8K | 41K |
| Input $ / M tokens | $2.50 | $0.037 |
| Output $ / M tokens | $10 | $0.17 |
| Results tracked | 24 | 48 |
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Category by category
Coding gpt-oss-120b leads
Command A: 27.2 (#322), gpt-oss-120b: 33.5 (#256)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| Aider Polyglot | 12% | 41.8% |
| LMArena Coding | 1330 | 1380 |
| SWE-bench Verified (bash only) | — | 26% |
| SciCode | — | 36% |
| WeirdML | — | 48.2% |
| ALE-Bench | — | 575.62 |
| AlgoTune | — | 1.41 |
Agentic & Tool Use Command A leads
Command A: 35.9 (#40), gpt-oss-120b: 12.2 (#153)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| Terminal-Bench | — | 18.7% |
| APEX-Agents | — | 4.4% |
| Berkeley Function Calling Leaderboard | 57.1% | — |
| METR Time Horizons | — | 56.6% |
| Vending-Bench 2 | — | -21.53 |
Reasoning gpt-oss-120b leads
Command A: 18.3 (#283), gpt-oss-120b: 20.0 (#245)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 58.6% |
| LMArena Hard Prompts | 1326 | 1364 |
| DTBench | 61.3% | 76.3% |
| LMCA | 10.3% | 22.1% |
| SimpleBench | — | 22.1% |
| CritPt | — | 1.1% |
| Chess Puzzles | — | 20% |
| Mystery Game Puzzles | — | 2% |
| Surface Evolver Bench | — | 25% |
| Epoch Capabilities Index | — | 139.93 |
Math gpt-oss-120b leads
Command A: 36.2 (#171), gpt-oss-120b: 52.5 (#50)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| LMArena Math | 1300 | 1389 |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| Omni-MATH | — | 68.8% |
Knowledge gpt-oss-120b leads
Command A: 37.1 (#159), gpt-oss-120b: 42.4 (#96)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 14.2% |
| LMArena Expert | 1295 | 1356 |
| GPQA Diamond | — | 75.8% |
| MMLU-Pro | — | 79.5% |
| Confabulations | — | 15.7% |
| GPQA (HELM) | — | 68.4% |
Multilingual gpt-oss-120b leads
Command A: 45.3 (#170), gpt-oss-120b: 48.0 (#147)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| LMArena Non-English | 1313 | 1351 |
| LMArena Chinese | 1327 | 1385 |
| LMArena French | 1351 | 1369 |
| LMArena German | 1341 | 1353 |
| LMArena Japanese | 1285 | 1331 |
| LMArena Korean | 1285 | 1282 |
| LMArena Russian | 1314 | 1343 |
| LMArena Spanish | 1347 | 1389 |
Instruction Following Too close to call
Command A: 69.1 (#177), gpt-oss-120b: 69.3 (#173)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| LMArena Instruction Following | 1309 | 1318 |
| IFEval | — | 83.6% |
Long Context Command A leads
Command A: 40.6 (#151), gpt-oss-120b: 31.4 (#278)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| LMArena Longer Query | 1334 | 1319 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference Command A leads
Command A: 47.6 (#208), gpt-oss-120b: 46.5 (#217)
| Benchmark | Command A | gpt-oss-120b |
|---|---|---|
| LMArena Text | 1331 | 1365 |
| LMArena Creative Writing | 1319 | 1275 |
| EQ-Bench Creative Writing | 1145 | 961 |
| LMArena Multi-Turn | 1339 | 1340 |
| Short-Story Creative Writing | — | 77.1% |
| WildBench | — | 84.5% |
Frequently asked questions
Is Command A better than gpt-oss-120b?
Command A and gpt-oss-120b score almost the same on the Noometry Index (36.5 vs 36.3), so choose on price, context window or the category you care about most.
Which is cheaper, Command A or gpt-oss-120b?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Command A lists at $2.50 and $10.
Is Command A or gpt-oss-120b better for coding?
gpt-oss-120b scores higher on coding benchmarks: 33.5 versus 27.2 in the Noometry coding category.
Which has the bigger context window?
Command A does, with 256K tokens against 131K.
How many benchmarks do Command A and gpt-oss-120b share?
23 benchmarks have published results for both models. Command A has 24 scored results on Noometry and gpt-oss-120b has 48.