Model comparison
GPT-4.1 nano vs Llama 4 Maverick
Llama 4 Maverick is the stronger model overall, scoring 30.9 to 27.9 on the Noometry Index. GPT-4.1 nano costs 1.7× less per token, which makes it the better buy when Llama 4 Maverick's lead doesn't matter for your workload.
Last verified . 37 shared benchmarks.
MetaSummary
- They share 37 benchmarks with published results for both. GPT-4.1 nano scores higher in 2 categories and Llama 4 Maverick in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama 4 Maverick leads 33.4 to 21.8.
- The biggest single-benchmark swing is MMLU-Pro: 55% for GPT-4.1 nano and 81% for Llama 4 Maverick.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.19 / $0.65 for Llama 4 Maverick.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 128K.
- Llama 4 Maverick has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 nano | Llama 4 Maverick | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 27.9 | 30.9 |
| Released | 2025-04-14 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 33K | 4K |
| Input $ / M tokens | $0.10 | $0.19 |
| Output $ / M tokens | $0.40 | $0.65 |
| Results tracked | 38 | 54 |
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Category by category
Coding Llama 4 Maverick leads
GPT-4.1 nano: 24.1 (#330), Llama 4 Maverick: 26.6 (#324)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| Aider Polyglot | 8.9% | 15.6% |
| SciCode | 25.9% | 33.1% |
| WeirdML | 19% | 24.5% |
| LMArena Coding | 1306 | 1302 |
| SWE-bench Verified (bash only) | — | 21% |
| BigCodeBench Instruct | — | 49.7% |
| BigCodeBench Complete | — | 61.4% |
| ALE-Bench | — | 172.97 |
Agentic & Tool Use Llama 4 Maverick leads
GPT-4.1 nano: 26.5 (#104), Llama 4 Maverick: 28.2 (#91)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| Berkeley Function Calling Leaderboard | 33% | 37.3% |
Reasoning Llama 4 Maverick leads
GPT-4.1 nano: 8.5 (#349), Llama 4 Maverick: 10.1 (#342)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| ARC-AGI-2 | 0% | 0% |
| Kagi LLM Benchmark | 33.3% | 55.9% |
| ARC-AGI-1 | 0% | 4.4% |
| CritPt | 0% | 0% |
| LMArena Hard Prompts | 1286 | 1281 |
| DTBench | 52.5% | 61.9% |
| LMCA | 5.5% | 15.9% |
| Epoch Capabilities Index | 129.62 | 132.2 |
| SimpleBench | — | 27.7% |
| NYT Connections (extended) | — | 8% |
| EnigmaEval | — | 0.6% |
| ForecastBench | — | 57.5 |
Math Too close to call
GPT-4.1 nano: 26.9 (#252), Llama 4 Maverick: 26.0 (#262)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 20.6% |
| Omni-MATH | 36.7% | 42.2% |
| LMArena Math | 1274 | 1299 |
| MATH Level 5 | 70% | 73% |
| FrontierMath (Feb 2025 set) | 1% | 0.7% |
Knowledge Llama 4 Maverick leads
GPT-4.1 nano: 21.8 (#273), Llama 4 Maverick: 33.4 (#204)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| GPQA Diamond | 48.9% | 67% |
| MMLU-Pro | 55% | 81% |
| GPQA (HELM) | 50.7% | 65% |
| LMArena Expert | 1272 | 1259 |
| Humanity's Last Exam | — | 5.7% |
| SimpleQA Verified | 6% | — |
| Confabulations | — | 22.6% |
| Vectara Hallucination Rate | — | 8.2% |
Multimodal Llama 4 Maverick leads
GPT-4.1 nano: 29.2 (#113), Llama 4 Maverick: 31.6 (#105)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| LMArena Vision | 1063 | 1142 |
| GeoBench | — | 52% |
| SpatialViz-Bench | — | 31.8% |
Multilingual Too close to call
GPT-4.1 nano: 41.6 (#205), Llama 4 Maverick: 42.2 (#195)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| LMArena Non-English | 1260 | 1269 |
| LMArena Chinese | 1270 | 1277 |
| LMArena German | 1288 | 1291 |
| LMArena Japanese | 1198 | 1207 |
| LMArena Russian | 1261 | 1286 |
| LMArena French | — | 1259 |
| LMArena Korean | — | 1203 |
| LMArena Spanish | — | 1293 |
Instruction Following Llama 4 Maverick leads
GPT-4.1 nano: 67.8 (#193), Llama 4 Maverick: 71.7 (#146)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| IFEval | 84.3% | 90.8% |
| LMArena Instruction Following | 1267 | 1267 |
Long Context Llama 4 Maverick leads
GPT-4.1 nano: 23.7 (#296), Llama 4 Maverick: 31.4 (#279)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| Fiction.LiveBench | 25% | 46.2% |
| LMArena Longer Query | 1283 | 1280 |
Writing & Preference GPT-4.1 nano leads
GPT-4.1 nano: 40.5 (#243), Llama 4 Maverick: 38.8 (#252)
| Benchmark | GPT-4.1 nano | Llama 4 Maverick |
|---|---|---|
| LMArena Text | 1285 | 1287 |
| LMArena Creative Writing | 1260 | 1267 |
| EQ-Bench Creative Writing | 946 | 860 |
| WildBench | 81.2% | 80% |
| LMArena Multi-Turn | 1277 | 1289 |
| Short-Story Creative Writing | — | 62% |
Frequently asked questions
Is GPT-4.1 nano better than Llama 4 Maverick?
Llama 4 Maverick is the stronger model overall, scoring 30.9 to 27.9 on the Noometry Index. GPT-4.1 nano costs 1.7× less per token, which makes it the better buy when Llama 4 Maverick's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or Llama 4 Maverick?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Llama 4 Maverick lists at $0.19 and $0.65.
Is GPT-4.1 nano or Llama 4 Maverick better for coding?
Llama 4 Maverick scores higher on coding benchmarks: 26.6 versus 24.1 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4.1 nano and Llama 4 Maverick share?
37 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Llama 4 Maverick has 54.