Model comparison
GPT-4.1 mini vs GPT-6 Astra
GPT-6 Astra is the stronger model overall, scoring 70.8 to 33.6 on the Noometry Index. GPT-4.1 mini costs 29× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Last verified . 33 shared benchmarks.
Summary
- They share 33 benchmarks with published results for both. GPT-4.1 mini scores higher in 0 categories and GPT-6 Astra in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Astra leads 85.1 to 10.8.
- The biggest single-benchmark swing is ARC-AGI-1: 3.5% for GPT-4.1 mini and 98.5% for GPT-6 Astra.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-4.1 mini | GPT-6 Astra | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 33.6 | 70.8 |
| Released | 2025-04-14 | 2026-09-03 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 33K | 128K |
| Input $ / M tokens | $0.40 | $10 |
| Output $ / M tokens | $1.60 | $50 |
| Results tracked | 47 | 56 |
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Category by category
Coding GPT-6 Astra leads
GPT-4.1 mini: 30.6 (#293), GPT-6 Astra: 73.7 (#2)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| SciCode | 40.4% | 56.5% |
| WeirdML | 37.6% | 93.6% |
| LMArena Coding | 1367 | 1487 |
| DeepSWE | — | 74.1% |
| FrontierCode | — | 53.3% |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| LMArena WebDev | — | 1786 |
| FrontierSWE | — | 65.5% |
| GSO | — | 79.4% |
| BigCodeBench Instruct | 48.9% | — |
| MirrorCode | — | 46.7% |
| CadEval | 16% | — |
| ALE-Bench | — | 2,951 |
Agentic & Tool Use GPT-6 Astra leads
GPT-4.1 mini: 33.3 (#55), GPT-6 Astra: 52.9 (#3)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| APEX-Agents | — | 64.7% |
| Berkeley Function Calling Leaderboard | 50.5% | — |
| Remote Labor Index | — | 20.8% |
| BALROG | — | 68.3% |
| GDP.pdf | — | 34.2% |
| Vending-Bench 2 | — | 15,515 |
Reasoning GPT-6 Astra leads
GPT-4.1 mini: 10.8 (#340), GPT-6 Astra: 85.1 (#1)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| ARC-AGI-2 | 0% | 95% |
| ARC-AGI-1 | 3.5% | 98.5% |
| CritPt | 0% | 31.7% |
| Chess Puzzles | 7% | 72% |
| LMArena Hard Prompts | 1349 | 1462 |
| Mystery Game Puzzles | 7% | 84% |
| DTBench | 68.8% | 97.3% |
| LMCA | 21.1% | 64.4% |
| Epoch Capabilities Index | 135.01 | 166.45 |
| Kagi LLM Benchmark | 48.6% | — |
| NYT Connections (extended) | — | 98.1% |
| EBR-Bench | — | 76.2% |
| Bench to the Future 3 | — | 0.14 |
Math GPT-6 Astra leads
GPT-4.1 mini: 24.1 (#270), GPT-6 Astra: 93.5 (#2)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | 93.7% |
| OTIS Mock AIME 2024-2025 | 44.7% | 100% |
| LMArena Math | 1343 | 1465 |
| FrontierMath Tier 4 | — | 97.6% |
| ProofBench | — | 99% |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Erdős | — | 2.9% |
Knowledge GPT-6 Astra leads
GPT-4.1 mini: 34.7 (#194), GPT-6 Astra: 75.3 (#1)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| GPQA Diamond | 65.8% | 95.8% |
| SimpleQA Verified | 12.7% | 75.6% |
| LMArena Expert | 1338 | 1483 |
| Humanity's Last Exam | — | 54.8% |
| MMLU-Pro | 78.3% | — |
| Vectara Hallucination Rate | — | 8.7% |
| GPQA (HELM) | 61.4% | — |
Multimodal GPT-6 Astra leads
GPT-4.1 mini: 35.8 (#82), GPT-6 Astra: 55.0 (#3)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| LMArena Vision | 1181 | 1281 |
| Blueprint-Bench 2 | — | 49.7% |
| Furniture Assembly | — | 80% |
| LMArena Document | — | 1468 |
Multilingual GPT-6 Astra leads
GPT-4.1 mini: 45.7 (#166), GPT-6 Astra: 53.7 (#61)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| LMArena Non-English | 1318 | 1430 |
| LMArena Chinese | 1329 | 1484 |
| LMArena French | 1358 | 1456 |
| LMArena German | 1351 | 1440 |
| LMArena Japanese | 1290 | 1379 |
| LMArena Korean | 1298 | 1426 |
| LMArena Russian | 1324 | 1436 |
| LMArena Spanish | 1319 | 1407 |
Instruction Following GPT-6 Astra leads
GPT-4.1 mini: 73.7 (#118), GPT-6 Astra: 76.3 (#44)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| LMArena Instruction Following | 1333 | 1450 |
| IFEval | 90.4% | — |
Long Context GPT-6 Astra leads
GPT-4.1 mini: 31.8 (#275), GPT-6 Astra: 44.5 (#62)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| LMArena Longer Query | 1344 | 1456 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference GPT-6 Astra leads
GPT-4.1 mini: 48.6 (#199), GPT-6 Astra: 75.3 (#7)
| Benchmark | GPT-4.1 mini | GPT-6 Astra |
|---|---|---|
| LMArena Text | 1340 | 1441 |
| LMArena Creative Writing | 1300 | 1418 |
| EQ-Bench Creative Writing | 1147 | 2173 |
| LMArena Multi-Turn | 1354 | 1448 |
| WildBench | 83.8% | — |
Frequently asked questions
Is GPT-4.1 mini better than GPT-6 Astra?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 33.6 on the Noometry Index. GPT-4.1 mini costs 29× 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-4.1 mini or GPT-6 Astra?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GPT-6 Astra lists at $10 and $50.
Is GPT-4.1 mini or GPT-6 Astra better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Astra does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 mini and GPT-6 Astra share?
33 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and GPT-6 Astra has 56.