Model comparison
GPT-6 Astra vs Grok 4.7
GPT-6 Astra is the stronger model overall, scoring 70.8 to 53.1 on the Noometry Index. Grok 4.7 costs 6.7× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Last verified . 38 shared benchmarks.
Summary
- They share 38 benchmarks with published results for both. GPT-6 Astra scores higher in 10 categories and Grok 4.7 in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Astra leads 85.1 to 49.1.
- The biggest single-benchmark swing is FrontierMath Tier 4: 97.6% for GPT-6 Astra and 17.1% for Grok 4.7.
- Grok 4.7 is cheaper at $2 / $6 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 500K.
Side by side
| GPT-6 Astra | Grok 4.7 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 70.8 | 53.1 |
| Released | 2026-09-03 | 2026-09-21 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 500K |
| Max output | 128K | 500K |
| Input $ / M tokens | $10 | $2 |
| Output $ / M tokens | $50 | $6 |
| Results tracked | 56 | 39 |
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Category by category
Coding GPT-6 Astra leads
GPT-6 Astra: 73.7 (#2), Grok 4.7: 58.0 (#18)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| FrontierCode | 53.3% | 47.6% |
| LMArena WebDev | 1786 | 1639 |
| FrontierSWE | 65.5% | 29.5% |
| SciCode | 56.5% | 57.8% |
| LMArena Coding | 1487 | 1427 |
| DeepSWE | 74.1% | — |
| CursorBench | — | 46.3% |
| GSO | 79.4% | — |
| WeirdML | 93.6% | — |
| MirrorCode | 46.7% | — |
| ALE-Bench | 2,951 | — |
Agentic & Tool Use GPT-6 Astra leads
GPT-6 Astra: 52.9 (#3), Grok 4.7: 36.7 (#37)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| APEX-Agents | 64.7% | 54.6% |
| GDP.pdf | 34.2% | 22.8% |
| Vending-Bench 2 | 15,515 | 10,537 |
| Remote Labor Index | 20.8% | — |
| BALROG | 68.3% | — |
Reasoning GPT-6 Astra leads
GPT-6 Astra: 85.1 (#1), Grok 4.7: 49.1 (#40)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| NYT Connections (extended) | 98.1% | 76.8% |
| CritPt | 31.7% | 18% |
| Chess Puzzles | 72% | 38% |
| LMArena Hard Prompts | 1462 | 1413 |
| Mystery Game Puzzles | 84% | 29% |
| DTBench | 97.3% | 96% |
| LMCA | 64.4% | 49.4% |
| Epoch Capabilities Index | 166.45 | 153.53 |
| ARC-AGI-2 | 95% | — |
| ARC-AGI-1 | 98.5% | — |
| EBR-Bench | 76.2% | — |
| Bench to the Future 3 | 0.14 | — |
Math GPT-6 Astra leads
GPT-6 Astra: 93.5 (#2), Grok 4.7: 57.8 (#39)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 93.7% | 53% |
| FrontierMath Tier 4 | 97.6% | 17.1% |
| OTIS Mock AIME 2024-2025 | 100% | 98.1% |
| ProofBench | 99% | 34% |
| LMArena Math | 1465 | 1407 |
| FrontierMath Erdős | 2.9% | — |
Knowledge GPT-6 Astra leads
GPT-6 Astra: 75.3 (#1), Grok 4.7: 62.8 (#22)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| GPQA Diamond | 95.8% | 92.7% |
| SimpleQA Verified | 75.6% | 56% |
| LMArena Expert | 1483 | 1422 |
| Humanity's Last Exam | 54.8% | — |
| Vectara Hallucination Rate | 8.7% | — |
Multimodal GPT-6 Astra leads
GPT-6 Astra: 55.0 (#3), Grok 4.7: 35.5 (#87)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| LMArena Vision | 1281 | 1228 |
| Blueprint-Bench 2 | 49.7% | 32.5% |
| Furniture Assembly | 80% | 20.8% |
| LMArena Document | 1468 | — |
Multilingual GPT-6 Astra leads
GPT-6 Astra: 53.7 (#61), Grok 4.7: 50.8 (#116)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| LMArena Non-English | 1430 | 1389 |
| LMArena Chinese | 1484 | 1455 |
| LMArena French | 1456 | 1455 |
| LMArena Russian | 1436 | 1397 |
| LMArena Spanish | 1407 | 1400 |
| LMArena German | 1440 | — |
| LMArena Japanese | 1379 | — |
| LMArena Korean | 1426 | — |
Instruction Following GPT-6 Astra leads
GPT-6 Astra: 76.3 (#44), Grok 4.7: 74.1 (#105)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| LMArena Instruction Following | 1450 | 1404 |
Long Context GPT-6 Astra leads
GPT-6 Astra: 44.5 (#62), Grok 4.7: 43.1 (#104)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| LMArena Longer Query | 1456 | 1413 |
Writing & Preference GPT-6 Astra leads
GPT-6 Astra: 75.3 (#7), Grok 4.7: 70.0 (#24)
| Benchmark | GPT-6 Astra | Grok 4.7 |
|---|---|---|
| LMArena Text | 1441 | 1399 |
| LMArena Creative Writing | 1418 | 1391 |
| EQ-Bench Creative Writing | 2173 | 2007 |
| LMArena Multi-Turn | 1448 | 1393 |
Frequently asked questions
Is GPT-6 Astra better than Grok 4.7?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 53.1 on the Noometry Index. Grok 4.7 costs 6.7× 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 Grok 4.7?
Grok 4.7 is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-6 Astra lists at $10 and $50.
Is GPT-6 Astra or Grok 4.7 better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 58.0 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Astra does, with 1.05M tokens against 500K.
How many benchmarks do GPT-6 Astra and Grok 4.7 share?
38 benchmarks have published results for both models. GPT-6 Astra has 56 scored results on Noometry and Grok 4.7 has 39.