Model comparison
Llama 4 Maverick vs o3
o3 is the stronger model overall, scoring 47.5 to 30.9 on the Noometry Index. Llama 4 Maverick costs 12× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 48 shared benchmarks.
MetaSummary
- They share 48 benchmarks with published results for both. Llama 4 Maverick scores higher in 0 categories and o3 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o3 leads 63.5 to 38.8.
- The biggest single-benchmark swing is Aider Polyglot: 15.6% for Llama 4 Maverick and 81.3% for o3.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $2 / $8 for o3.
- o3 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 | o3 | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 30.9 | 47.5 |
| Released | 2025-04-05 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | 128K | 200K |
| Max output | 4K | 100K |
| Input $ / M tokens | $0.19 | $2 |
| Output $ / M tokens | $0.65 | $8 |
| Results tracked | 54 | 63 |
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Category by category
Coding o3 leads
Llama 4 Maverick: 26.6 (#324), o3: 46.8 (#64)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| SWE-bench Verified (bash only) | 21% | 58.4% |
| Aider Polyglot | 15.6% | 81.3% |
| WeirdML | 24.5% | 52.4% |
| LMArena Coding | 1302 | 1408 |
| ALE-Bench | 172.97 | 933.55 |
| SWE-bench Verified | — | 62.3% |
| SciCode | 33.1% | — |
| GSO | — | 8.8% |
| BigCodeBench Instruct | 49.7% | — |
| BigCodeBench Complete | 61.4% | — |
| CadEval | — | 74% |
Agentic & Tool Use o3 leads
Llama 4 Maverick: 28.2 (#91), o3: 34.5 (#44)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
Reasoning o3 leads
Llama 4 Maverick: 10.1 (#342), o3: 32.0 (#78)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| ARC-AGI-2 | 0% | 6.5% |
| SimpleBench | 27.7% | 53.1% |
| Kagi LLM Benchmark | 55.9% | 67.6% |
| ARC-AGI-1 | 4.4% | 60.8% |
| CritPt | 0% | 1.4% |
| EnigmaEval | 0.6% | 13.1% |
| LMArena Hard Prompts | 1281 | 1402 |
| DTBench | 61.9% | 84.8% |
| LMCA | 15.9% | 39.7% |
| Epoch Capabilities Index | 132.2 | 146.86 |
| ForecastBench | 57.5 | 62.5 |
| NYT Connections (extended) | 8% | — |
| Chess Puzzles | — | 38% |
| Mystery Game Puzzles | — | 29% |
Math o3 leads
Llama 4 Maverick: 26.0 (#262), o3: 50.2 (#58)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 20.6% | 84.4% |
| Omni-MATH | 42.2% | 71.4% |
| LMArena Math | 1299 | 1426 |
| MATH Level 5 | 73% | 97.8% |
| FrontierMath (Feb 2025 set) | 0.7% | 18.7% |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge o3 leads
Llama 4 Maverick: 33.4 (#204), o3: 54.6 (#52)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| GPQA Diamond | 67% | 81.8% |
| Humanity's Last Exam | 5.7% | 20.3% |
| MMLU-Pro | 81% | 85.9% |
| Confabulations | 22.6% | 14.4% |
| GPQA (HELM) | 65% | 75.3% |
| LMArena Expert | 1259 | 1402 |
| SimpleQA Verified | — | 49.4% |
| Vectara Hallucination Rate | 8.2% | — |
Multimodal o3 leads
Llama 4 Maverick: 31.6 (#105), o3: 41.4 (#36)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| LMArena Vision | 1142 | 1214 |
| GeoBench | 52% | 74% |
| VPCT | — | 52% |
| SpatialViz-Bench | 31.8% | — |
Multilingual o3 leads
Llama 4 Maverick: 42.2 (#195), o3: 51.7 (#105)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| LMArena Non-English | 1269 | 1401 |
| LMArena Chinese | 1277 | 1437 |
| LMArena French | 1259 | 1430 |
| LMArena German | 1291 | 1420 |
| LMArena Japanese | 1207 | 1403 |
| LMArena Korean | 1203 | 1370 |
| LMArena Russian | 1286 | 1406 |
| LMArena Spanish | 1293 | 1395 |
Instruction Following o3 leads
Llama 4 Maverick: 71.7 (#146), o3: 72.8 (#127)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| IFEval | 90.8% | 86.9% |
| LMArena Instruction Following | 1267 | 1368 |
Long Context o3 leads
Llama 4 Maverick: 31.4 (#279), o3: 53.3 (#6)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| Fiction.LiveBench | 46.2% | 88.9% |
| LMArena Longer Query | 1280 | 1372 |
| CL-bench | — | 17.8% |
Writing & Preference o3 leads
Llama 4 Maverick: 38.8 (#252), o3: 63.5 (#64)
| Benchmark | Llama 4 Maverick | o3 |
|---|---|---|
| LMArena Text | 1287 | 1410 |
| LMArena Creative Writing | 1267 | 1359 |
| Short-Story Creative Writing | 62% | 83.9% |
| EQ-Bench Creative Writing | 860 | 1676 |
| WildBench | 80% | 86.1% |
| LMArena Multi-Turn | 1289 | 1405 |
Frequently asked questions
Is Llama 4 Maverick better than o3?
o3 is the stronger model overall, scoring 47.5 to 30.9 on the Noometry Index. Llama 4 Maverick costs 12× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Maverick or o3?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; o3 lists at $2 and $8.
Is Llama 4 Maverick or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 26.6 in the Noometry coding category.
Which has the bigger context window?
o3 does, with 200K tokens against 128K.
How many benchmarks do Llama 4 Maverick and o3 share?
48 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and o3 has 63.