Model comparison
Llama 4 Maverick vs o1
o1 is the stronger model overall, scoring 40.6 to 30.6 on the Noometry Index. Llama 4 Maverick costs 86× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Last verified . 36 shared benchmarks.
MetaSummary
- They share 36 benchmarks with published results for both. Llama 4 Maverick scores higher in 1 category and o1 in 9 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in coding, where o1 leads 45.7 to 26.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 20.6% for Llama 4 Maverick and 73.3% for o1.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $15 / $60 for o1.
- o1 accepts more context: 200K tokens versus 128K.
- Llama 4 Maverick has downloadable open weights; the other is API-only.
Side by side
| Llama 4 Maverick | o1 | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 30.6 | 40.6 |
| Released | 2025-04-05 | 2024-09-12 |
| Weights | Open | Proprietary |
| Context window | 128K | 200K |
| Max output | 4K | 100K |
| Input $ / M tokens | $0.19 | $15 |
| Output $ / M tokens | $0.65 | $60 |
| Results tracked | 54 | 52 |
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Category by category
Coding o1 leads
Llama 4 Maverick: 26.3 (#318), o1: 45.7 (#64)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| Aider Polyglot | 15.6% | 61.7% |
| WeirdML | 24.5% | 47.6% |
| LMArena Coding | 1302 | 1367 |
| SWE-bench Verified (bash only) | 21% | — |
| SciCode | 33.1% | — |
| BigCodeBench Instruct | 49.7% | — |
| LiveBench Coding | — | 69.7% |
| BigCodeBench Complete | 61.4% | — |
| CadEval | — | 56% |
| ALE-Bench | 172.97 | — |
| HumanEval+ | — | 89% |
| MBPP+ | — | 80.2% |
Agentic & Tool Use Llama 4 Maverick leads
Llama 4 Maverick: 27.9 (#86), o1: 24.3 (#111)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | — |
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |
Reasoning o1 leads
Llama 4 Maverick: 10.1 (#337), o1: 27.5 (#103)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| SimpleBench | 27.7% | 41.7% |
| ARC-AGI-1 | 4.4% | 30.7% |
| EnigmaEval | 0.6% | 5.7% |
| LMArena Hard Prompts | 1281 | 1372 |
| DTBench | 61.9% | 74.7% |
| LMCA | 15.9% | 22.3% |
| Epoch Capabilities Index | 132.2 | 141.92 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 55.9% | — |
| NYT Connections (extended) | 8% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 15% |
| LiveBench Reasoning | — | 91.6% |
| LiveBench Data Analysis | — | 65.5% |
| ForecastBench | 57.5 | — |
| LiveBench | — | 75.7% |
Math o1 leads
Llama 4 Maverick: 24.6 (#256), o1: 34.9 (#150)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 20.6% | 73.3% |
| LMArena Math | 1299 | 1388 |
| MATH Level 5 | 73% | 94.7% |
| FrontierMath (Feb 2025 set) | 0.7% | 9.3% |
| FrontierMath (Tiers 1-3) | — | 14.7% |
| Omni-MATH | 42.2% | — |
| LiveBench Math | — | 80.3% |
Knowledge o1 leads
Llama 4 Maverick: 33.3 (#196), o1: 41.5 (#101)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| GPQA Diamond | 67% | 76.8% |
| Humanity's Last Exam | 5.7% | 8% |
| Confabulations | 22.6% | 11.7% |
| LMArena Expert | 1259 | 1362 |
| SimpleQA Verified | — | 41.1% |
| MMLU-Pro | 81% | — |
| Vectara Hallucination Rate | 8.2% | — |
| GPQA (HELM) | 65% | — |
Multimodal o1 leads
Llama 4 Maverick: 30.9 (#100), o1: 33.6 (#87)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| LMArena Vision | 1141 | 1168 |
| GeoBench | 52% | 80% |
| SpatialViz-Bench | 31.8% | 41.4% |
| VPCT | — | 37% |
Multilingual o1 leads
Llama 4 Maverick: 42.4 (#190), o1: 48.8 (#137)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| LMArena Non-English | 1269 | 1359 |
| LMArena Chinese | 1277 | 1394 |
| LMArena French | 1258 | 1343 |
| LMArena German | 1291 | 1337 |
| LMArena Japanese | 1207 | 1346 |
| LMArena Korean | 1203 | 1396 |
| LMArena Russian | 1286 | 1356 |
| LMArena Spanish | 1293 | 1345 |
Instruction Following o1 leads
Llama 4 Maverick: 71.9 (#140), o1: 75.0 (#82)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1368 |
| LiveBench Instruction Following | — | 81.5% |
| IFEval | 90.8% | — |
Long Context o1 leads
Llama 4 Maverick: 31.4 (#274), o1: 50.3 (#9)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| Fiction.LiveBench | 46.2% | 83.3% |
| LMArena Longer Query | 1280 | 1378 |
Writing & Preference o1 leads
Llama 4 Maverick: 39.0 (#247), o1: 55.8 (#139)
| Benchmark | Llama 4 Maverick | o1 |
|---|---|---|
| LMArena Text | 1287 | 1366 |
| LMArena Creative Writing | 1266 | 1347 |
| Short-Story Creative Writing | 62% | 70.2% |
| LMArena Multi-Turn | 1289 | 1368 |
| EQ-Bench Creative Writing | 860 | — |
| WildBench | 80% | — |
| LiveBench Language | — | 65.4% |
Frequently asked questions
Is Llama 4 Maverick better than o1?
o1 is the stronger model overall, scoring 40.6 to 30.6 on the Noometry Index. Llama 4 Maverick costs 86× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Maverick or o1?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; o1 lists at $15 and $60.
Is Llama 4 Maverick or o1 better for coding?
o1 scores higher on coding benchmarks: 45.7 versus 26.3 in the Noometry coding category.
Which has the bigger context window?
o1 does, with 200K tokens against 128K.
How many benchmarks do Llama 4 Maverick and o1 share?
36 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and o1 has 52.