Model comparison
GPT-6 Astra vs Llama 4 Maverick
GPT-6 Astra is the stronger model overall, scoring 70.3 to 30.6 on the Noometry Index. Llama 4 Maverick costs 66× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Last verified . 30 shared benchmarks.
Summary
- They share 30 benchmarks with published results for both. GPT-6 Astra scores higher in 10 categories and Llama 4 Maverick in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Astra leads 85.1 to 10.1.
- The biggest single-benchmark swing is ARC-AGI-2: 95% for GPT-6 Astra and 0% for Llama 4 Maverick.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 128K.
- Llama 4 Maverick has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Astra | Llama 4 Maverick | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 70.3 | 30.6 |
| Released | 2026-09-03 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $10 | $0.19 |
| Output $ / M tokens | $50 | $0.65 |
| Results tracked | 51 | 54 |
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Category by category
Coding GPT-6 Astra leads
GPT-6 Astra: 70.5 (#3), Llama 4 Maverick: 26.3 (#318)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| SciCode | 56.5% | 33.1% |
| WeirdML | 93.6% | 24.5% |
| LMArena Coding | 1488 | 1302 |
| ALE-Bench | 2,951 | 172.97 |
| DeepSWE | 74.1% | — |
| FrontierCode | 53.3% | — |
| SWE-bench Verified (bash only) | — | 21% |
| Aider Polyglot | — | 15.6% |
| LMArena WebDev | 1792 | — |
| FrontierSWE | 65.5% | — |
| BigCodeBench Instruct | — | 49.7% |
| MirrorCode | 46.7% | — |
| BigCodeBench Complete | — | 61.4% |
Agentic & Tool Use GPT-6 Astra leads
GPT-6 Astra: 52.3 (#3), Llama 4 Maverick: 27.9 (#86)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| APEX-Agents | 64.7% | — |
| Berkeley Function Calling Leaderboard | — | 37.3% |
| Remote Labor Index | 20.8% | — |
| BALROG | 68.3% | — |
| Vending-Bench 2 | 15,515 | — |
Reasoning GPT-6 Astra leads
GPT-6 Astra: 85.1 (#1), Llama 4 Maverick: 10.1 (#337)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| ARC-AGI-2 | 95% | 0% |
| NYT Connections (extended) | 98.1% | 8% |
| ARC-AGI-1 | 98.5% | 4.4% |
| CritPt | 31.7% | 0% |
| LMArena Hard Prompts | 1464 | 1281 |
| DTBench | 97.3% | 61.9% |
| LMCA | 64.4% | 15.9% |
| Epoch Capabilities Index | 166.6 | 132.2 |
| SimpleBench | — | 27.7% |
| Kagi LLM Benchmark | — | 55.9% |
| Chess Puzzles | 72% | — |
| EnigmaEval | — | 0.6% |
| EBR-Bench | 76.2% | — |
| Mystery Game Puzzles | 84% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | — | 57.5 |
Math GPT-6 Astra leads
GPT-6 Astra: 93.4 (#1), Llama 4 Maverick: 24.6 (#256)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 20.6% |
| LMArena Math | 1463 | 1299 |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 97.6% | — |
| ProofBench | 99% | — |
| Omni-MATH | — | 42.2% |
| MATH Level 5 | — | 73% |
| FrontierMath (Feb 2025 set) | — | 0.7% |
| FrontierMath Erdős | 2.9% | — |
Knowledge GPT-6 Astra leads
GPT-6 Astra: 75.3 (#1), Llama 4 Maverick: 33.3 (#196)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| GPQA Diamond | 95.8% | 67% |
| Humanity's Last Exam | 54.8% | 5.7% |
| Vectara Hallucination Rate | 8.7% | 8.2% |
| LMArena Expert | 1486 | 1259 |
| SimpleQA Verified | 75.6% | — |
| MMLU-Pro | — | 81% |
| Confabulations | — | 22.6% |
| GPQA (HELM) | — | 65% |
Multimodal GPT-6 Astra leads
GPT-6 Astra: 55.1 (#3), Llama 4 Maverick: 30.9 (#100)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| LMArena Vision | 1280 | 1141 |
| GeoBench | — | 52% |
| Blueprint-Bench 2 | 49.7% | — |
| Furniture Assembly | 80% | — |
| LMArena Document | 1468 | — |
| SpatialViz-Bench | — | 31.8% |
Multilingual GPT-6 Astra leads
GPT-6 Astra: 54.0 (#53), Llama 4 Maverick: 42.4 (#190)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| LMArena Non-English | 1431 | 1269 |
| LMArena Chinese | 1495 | 1277 |
| LMArena French | 1467 | 1258 |
| LMArena Russian | 1434 | 1286 |
| LMArena Spanish | 1412 | 1293 |
| LMArena German | — | 1291 |
| LMArena Japanese | — | 1207 |
| LMArena Korean | — | 1203 |
Instruction Following GPT-6 Astra leads
GPT-6 Astra: 76.6 (#37), Llama 4 Maverick: 71.9 (#140)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| LMArena Instruction Following | 1454 | 1267 |
| IFEval | — | 90.8% |
Long Context GPT-6 Astra leads
GPT-6 Astra: 44.7 (#57), Llama 4 Maverick: 31.4 (#274)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| LMArena Longer Query | 1460 | 1280 |
| Fiction.LiveBench | — | 46.2% |
Writing & Preference GPT-6 Astra leads
GPT-6 Astra: 75.7 (#7), Llama 4 Maverick: 39.0 (#247)
| Benchmark | GPT-6 Astra | Llama 4 Maverick |
|---|---|---|
| LMArena Text | 1443 | 1287 |
| LMArena Creative Writing | 1423 | 1266 |
| EQ-Bench Creative Writing | 2173 | 860 |
| LMArena Multi-Turn | 1457 | 1289 |
| Short-Story Creative Writing | — | 62% |
| WildBench | — | 80% |
Frequently asked questions
Is GPT-6 Astra better than Llama 4 Maverick?
GPT-6 Astra is the stronger model overall, scoring 70.3 to 30.6 on the Noometry Index. Llama 4 Maverick costs 66× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Astra or Llama 4 Maverick?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; GPT-6 Astra lists at $10 and $50.
Is GPT-6 Astra or Llama 4 Maverick better for coding?
GPT-6 Astra scores higher on coding benchmarks: 70.5 versus 26.3 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Astra does, with 1.05M tokens against 128K.
How many benchmarks do GPT-6 Astra and Llama 4 Maverick share?
30 benchmarks have published results for both models. GPT-6 Astra has 51 scored results on Noometry and Llama 4 Maverick has 54.