Model comparison
GPT-6 Astra vs Llama 2-70B
GPT-6 Astra is the stronger model overall, scoring 70.8 to 24.4 on the Noometry Index.
Last verified . 21 shared benchmarks.
MetaSummary
- They share 21 benchmarks with published results for both. GPT-6 Astra scores higher in 8 categories and Llama 2-70B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.5 to 8.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 100% for GPT-6 Astra and 0% for Llama 2-70B.
- Llama 2-70B has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Astra | Llama 2-70B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 70.8 | 24.4 |
| Released | 2026-09-03 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $10 | — |
| Output $ / M tokens | $50 | — |
| Results tracked | 56 | 35 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Astra leads
GPT-6 Astra: 73.7 (#2), Llama 2-70B: 31.4 (#286)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| LMArena Coding | 1487 | 1079 |
| DeepSWE | 74.1% | — |
| FrontierCode | 53.3% | — |
| LMArena WebDev | 1786 | — |
| FrontierSWE | 65.5% | — |
| SciCode | 56.5% | — |
| GSO | 79.4% | — |
| WeirdML | 93.6% | — |
| MirrorCode | 46.7% | — |
| ALE-Bench | 2,951 | — |
Agentic & Tool Use Not comparable
GPT-6 Astra: 52.9 (#3), Llama 2-70B: —
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| APEX-Agents | 64.7% | — |
| Remote Labor Index | 20.8% | — |
| BALROG | 68.3% | — |
| GDP.pdf | 34.2% | — |
| Vending-Bench 2 | 15,515 | — |
Reasoning GPT-6 Astra leads
GPT-6 Astra: 85.1 (#1), Llama 2-70B: 14.4 (#325)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| LMArena Hard Prompts | 1462 | 1073 |
| DTBench | 97.3% | 41.6% |
| Epoch Capabilities Index | 166.45 | 113.79 |
| ARC-AGI-2 | 95% | — |
| NYT Connections (extended) | 98.1% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| Chess Puzzles | 72% | — |
| EBR-Bench | 76.2% | — |
| Mystery Game Puzzles | 84% | — |
| LMCA | 64.4% | — |
| Bench to the Future 3 | 0.14 | — |
| BIG-Bench Hard | — | 64.9% |
| CommonsenseQA 2.0 | — | 50% |
| ForecastBench | — | 51.4 |
| HellaSwag | — | 85.3% |
| LAMBADA | — | 78.9% |
| PIQA | — | 82.8% |
| WinoGrande | — | 80.2% |
Math GPT-6 Astra leads
GPT-6 Astra: 93.5 (#2), Llama 2-70B: 8.1 (#326)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 0% |
| LMArena Math | 1465 | 1091 |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 97.6% | — |
| ProofBench | 99% | — |
| MATH Level 5 | — | 3.3% |
| FrontierMath Erdős | 2.9% | — |
| GSM8K | — | 69.6% |
Knowledge GPT-6 Astra leads
GPT-6 Astra: 75.3 (#1), Llama 2-70B: 7.4 (#310)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| GPQA Diamond | 95.8% | 26.3% |
| LMArena Expert | 1483 | 1039 |
| Humanity's Last Exam | 54.8% | — |
| SimpleQA Verified | 75.6% | — |
| Vectara Hallucination Rate | 8.7% | — |
| ARC (AI2) Challenge | — | 78.3% |
| BoolQ | — | 88.6% |
| MMLU | — | 69.9% |
| OpenBookQA | — | 60.2% |
| TriviaQA | — | 87.6% |
Multimodal Not comparable
GPT-6 Astra: 55.0 (#3), Llama 2-70B: —
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| LMArena Vision | 1281 | — |
| Blueprint-Bench 2 | 49.7% | — |
| Furniture Assembly | 80% | — |
| LMArena Document | 1468 | — |
Multilingual GPT-6 Astra leads
GPT-6 Astra: 53.7 (#61), Llama 2-70B: 27.7 (#274)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| LMArena Non-English | 1430 | 1045 |
| LMArena Chinese | 1484 | 995 |
| LMArena French | 1456 | 1090 |
| LMArena German | 1440 | 1041 |
| LMArena Japanese | 1379 | 927 |
| LMArena Korean | 1426 | 964 |
| LMArena Russian | 1436 | 1083 |
| LMArena Spanish | 1407 | 1143 |
Instruction Following GPT-6 Astra leads
GPT-6 Astra: 76.3 (#44), Llama 2-70B: 54.9 (#278)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| LMArena Instruction Following | 1450 | 1071 |
Long Context GPT-6 Astra leads
GPT-6 Astra: 44.5 (#62), Llama 2-70B: 32.3 (#270)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| LMArena Longer Query | 1456 | 1062 |
Writing & Preference GPT-6 Astra leads
GPT-6 Astra: 75.3 (#7), Llama 2-70B: 32.3 (#279)
| Benchmark | GPT-6 Astra | Llama 2-70B |
|---|---|---|
| LMArena Text | 1441 | 1115 |
| LMArena Creative Writing | 1418 | 1075 |
| LMArena Multi-Turn | 1448 | 1088 |
| EQ-Bench Creative Writing | 2173 | — |
Frequently asked questions
Is GPT-6 Astra better than Llama 2-70B?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 24.4 on the Noometry Index.
Is GPT-6 Astra or Llama 2-70B better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 31.4 in the Noometry coding category.
How many benchmarks do GPT-6 Astra and Llama 2-70B share?
21 benchmarks have published results for both models. GPT-6 Astra has 56 scored results on Noometry and Llama 2-70B has 35.