Model comparison
GPT-6 Astra vs Llama 3.2 90B
GPT-6 Astra is the stronger model overall, scoring 70.8 to 27.5 on the Noometry Index.
Last verified . 5 shared benchmarks.
Summary
- They share 5 benchmarks with published results for both. GPT-6 Astra scores higher in 5 categories and Llama 3.2 90B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.5 to 11.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 100% for GPT-6 Astra and 2.6% for Llama 3.2 90B.
- Llama 3.2 90B has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Astra | Llama 3.2 90B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 70.8 | 27.5 |
| Released | 2026-09-03 | 2024-09-24 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $10 | — |
| Output $ / M tokens | $50 | — |
| Results tracked | 56 | 9 |
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Category by category
Coding Not comparable
GPT-6 Astra: 73.7 (#2), Llama 3.2 90B: —
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| DeepSWE | 74.1% | — |
| FrontierCode | 53.3% | — |
| LMArena WebDev | 1786 | — |
| FrontierSWE | 65.5% | — |
| SciCode | 56.5% | — |
| GSO | 79.4% | — |
| WeirdML | 93.6% | — |
| LMArena Coding | 1487 | — |
| MirrorCode | 46.7% | — |
| ALE-Bench | 2,951 | — |
Agentic & Tool Use GPT-6 Astra leads
GPT-6 Astra: 52.9 (#3), Llama 3.2 90B: 30.0 (#80)
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| BALROG | 68.3% | 27.3% |
| APEX-Agents | 64.7% | — |
| Remote Labor Index | 20.8% | — |
| GDP.pdf | 34.2% | — |
| Vending-Bench 2 | 15,515 | — |
Reasoning GPT-6 Astra leads
GPT-6 Astra: 85.1 (#1), Llama 3.2 90B: 21.7 (#217)
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| Epoch Capabilities Index | 166.45 | 125.5 |
| ARC-AGI-2 | 95% | — |
| NYT Connections (extended) | 98.1% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| Chess Puzzles | 72% | — |
| EnigmaEval | — | 0.4% |
| EBR-Bench | 76.2% | — |
| LMArena Hard Prompts | 1462 | — |
| Mystery Game Puzzles | 84% | — |
| DTBench | 97.3% | — |
| LMCA | 64.4% | — |
| Bench to the Future 3 | 0.14 | — |
Math GPT-6 Astra leads
GPT-6 Astra: 93.5 (#2), Llama 3.2 90B: 11.1 (#308)
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 2.6% |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 97.6% | — |
| ProofBench | 99% | — |
| LMArena Math | 1465 | — |
| MATH Level 5 | — | 39.4% |
| FrontierMath Erdős | 2.9% | — |
Knowledge GPT-6 Astra leads
GPT-6 Astra: 75.3 (#1), Llama 3.2 90B: 21.7 (#274)
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| GPQA Diamond | 95.8% | 41% |
| Humanity's Last Exam | 54.8% | — |
| SimpleQA Verified | 75.6% | — |
| Vectara Hallucination Rate | 8.7% | — |
| LMArena Expert | 1483 | — |
| MMLU | — | 80.3% |
Multimodal GPT-6 Astra leads
GPT-6 Astra: 55.0 (#3), Llama 3.2 90B: 25.4 (#124)
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| LMArena Vision | 1281 | 1000 |
| GeoBench | — | 52% |
| Blueprint-Bench 2 | 49.7% | — |
| Furniture Assembly | 80% | — |
| LMArena Document | 1468 | — |
Multilingual Not comparable
GPT-6 Astra: 53.7 (#61), Llama 3.2 90B: —
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| LMArena Non-English | 1430 | — |
| LMArena Chinese | 1484 | — |
| LMArena French | 1456 | — |
| LMArena German | 1440 | — |
| LMArena Japanese | 1379 | — |
| LMArena Korean | 1426 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1407 | — |
Instruction Following Not comparable
GPT-6 Astra: 76.3 (#44), Llama 3.2 90B: —
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| LMArena Instruction Following | 1450 | — |
Long Context Not comparable
GPT-6 Astra: 44.5 (#62), Llama 3.2 90B: —
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| LMArena Longer Query | 1456 | — |
Writing & Preference Not comparable
GPT-6 Astra: 75.3 (#7), Llama 3.2 90B: —
| Benchmark | GPT-6 Astra | Llama 3.2 90B |
|---|---|---|
| LMArena Text | 1441 | — |
| LMArena Creative Writing | 1418 | — |
| EQ-Bench Creative Writing | 2173 | — |
| LMArena Multi-Turn | 1448 | — |
Frequently asked questions
Is GPT-6 Astra better than Llama 3.2 90B?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 27.5 on the Noometry Index.
How many benchmarks do GPT-6 Astra and Llama 3.2 90B share?
5 benchmarks have published results for both models. GPT-6 Astra has 56 scored results on Noometry and Llama 3.2 90B has 9.