Model comparison
GPT-5.5 vs GPT-6 Astra
GPT-6 Astra is the stronger model overall, scoring 70.8 to 63.4 on the Noometry Index. GPT-5.5 costs 1.8× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Last verified . 53 shared benchmarks.
Summary
- They share 53 benchmarks with published results for both. GPT-5.5 scores higher in 3 categories and GPT-6 Astra in 7 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-6 Astra leads 73.7 to 58.2.
- The biggest single-benchmark swing is ProofBench: 50% for GPT-5.5 and 99% for GPT-6 Astra.
- GPT-5.5 is cheaper at $5 / $30 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
Side by side
| GPT-5.5 | GPT-6 Astra | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 63.4 | 70.8 |
| Released | 2026-04-23 | 2026-09-03 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $5 | $10 |
| Output $ / M tokens | $30 | $50 |
| Results tracked | 71 | 56 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Astra leads
GPT-5.5: 58.2 (#17), GPT-6 Astra: 73.7 (#2)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| DeepSWE | 67% | 74.1% |
| FrontierCode | 43% | 53.3% |
| LMArena WebDev | 1513 | 1786 |
| SciCode | 56.1% | 56.5% |
| GSO | 40.2% | 79.4% |
| WeirdML | 84.9% | 93.6% |
| LMArena Coding | 1494 | 1487 |
| MirrorCode | 10% | 46.7% |
| ALE-Bench | 1,943 | 2,951 |
| SWE-bench Verified | 80.6% | — |
| FrontierSWE | — | 65.5% |
Agentic & Tool Use GPT-6 Astra leads
GPT-5.5: 50.7 (#6), GPT-6 Astra: 52.9 (#3)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| APEX-Agents | 55.1% | 64.7% |
| Remote Labor Index | 6.3% | 20.8% |
| GDP.pdf | 26% | 34.2% |
| Vending-Bench 2 | 7,524 | 15,515 |
| Terminal-Bench | 84.7% | — |
| OSWorld 2.0 | 13% | — |
| τ²-bench Banking | 44.6% | — |
| DeepResearch Bench | 54% | — |
| PostTrainBench | 27.2% | — |
| BALROG | — | 68.3% |
| ExploitBench | 47.4% | — |
| GBAEval | 53.2% | — |
| LMArena Search | 1242 | — |
Reasoning GPT-6 Astra leads
GPT-5.5: 72.8 (#11), GPT-6 Astra: 85.1 (#1)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| ARC-AGI-2 | 85% | 95% |
| NYT Connections (extended) | 96.2% | 98.1% |
| ARC-AGI-1 | 95% | 98.5% |
| CritPt | 27.1% | 31.7% |
| Chess Puzzles | 54% | 72% |
| EBR-Bench | 34.3% | 76.2% |
| LMArena Hard Prompts | 1489 | 1462 |
| Mystery Game Puzzles | 56% | 84% |
| DTBench | 96% | 97.3% |
| LMCA | 54.3% | 64.4% |
| Bench to the Future 3 | 0.14 | 0.14 |
| Epoch Capabilities Index | 159.1 | 166.45 |
| SimpleBench | 69% | — |
| Kagi LLM Benchmark | 88.8% | — |
| Surface Evolver Bench | 88.1% | — |
| ForecastBench | 60.6 | — |
Math GPT-6 Astra leads
GPT-5.5: 81.7 (#11), GPT-6 Astra: 93.5 (#2)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 85.3% | 93.7% |
| FrontierMath Tier 4 | 72.5% | 97.6% |
| OTIS Mock AIME 2024-2025 | 100% | 100% |
| ProofBench | 50% | 99% |
| LMArena Math | 1486 | 1465 |
| FrontierMath Erdős | 0% | 2.9% |
| MathArena Final-Answer Competitions | 94.3% | — |
| FrontierMath (Feb 2025 set) | 51.7% | — |
| FrontierMath Tier 4 (v1) | 35.4% | — |
Knowledge GPT-6 Astra leads
GPT-5.5: 64.4 (#17), GPT-6 Astra: 75.3 (#1)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| GPQA Diamond | 94% | 95.8% |
| SimpleQA Verified | 63% | 75.6% |
| Vectara Hallucination Rate | 9.3% | 8.7% |
| LMArena Expert | 1508 | 1483 |
| Humanity's Last Exam | — | 54.8% |
Multimodal GPT-6 Astra leads
GPT-5.5: 46.9 (#12), GPT-6 Astra: 55.0 (#3)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Vision | 1297 | 1281 |
| Blueprint-Bench 2 | 36.2% | 49.7% |
| Furniture Assembly | 44.2% | 80% |
| LMArena Document | 1486 | 1468 |
Multilingual GPT-5.5 leads
GPT-5.5: 56.4 (#20), GPT-6 Astra: 53.7 (#61)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Non-English | 1467 | 1430 |
| LMArena Chinese | 1533 | 1484 |
| LMArena French | 1486 | 1456 |
| LMArena German | 1480 | 1440 |
| LMArena Japanese | 1498 | 1379 |
| LMArena Korean | 1460 | 1426 |
| LMArena Russian | 1473 | 1436 |
| LMArena Spanish | 1468 | 1407 |
Instruction Following GPT-5.5 leads
GPT-5.5: 77.5 (#18), GPT-6 Astra: 76.3 (#44)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Instruction Following | 1479 | 1450 |
Long Context GPT-5.5 leads
GPT-5.5: 48.3 (#12), GPT-6 Astra: 44.5 (#62)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Longer Query | 1484 | 1456 |
| CL-bench Life | 22.2% | — |
Writing & Preference GPT-6 Astra leads
GPT-5.5: 72.7 (#13), GPT-6 Astra: 75.3 (#7)
| Benchmark | GPT-5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Text | 1472 | 1441 |
| LMArena Creative Writing | 1455 | 1418 |
| EQ-Bench Creative Writing | 1844 | 2173 |
| LMArena Multi-Turn | 1476 | 1448 |
| EQ-Bench 4 | 1315 | — |
Frequently asked questions
Is GPT-5.5 better than GPT-6 Astra?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 63.4 on the Noometry Index. GPT-5.5 costs 1.8× 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-5.5 or GPT-6 Astra?
GPT-5.5 is cheaper. It lists at $5 per million input tokens and $30 per million output tokens; GPT-6 Astra lists at $10 and $50.
Is GPT-5.5 or GPT-6 Astra better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 58.2 in the Noometry coding category.
Which has the bigger context window?
Both accept 1.05M tokens.
How many benchmarks do GPT-5.5 and GPT-6 Astra share?
53 benchmarks have published results for both models. GPT-5.5 has 71 scored results on Noometry and GPT-6 Astra has 56.