Model comparison
GPT-4.1 mini vs GPT-5.6 Sol
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 33.6 on the Noometry Index. GPT-4.1 mini costs 11× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.
Last verified . 34 shared benchmarks.
Summary
- They share 34 benchmarks with published results for both. GPT-4.1 mini scores higher in 0 categories and GPT-5.6 Sol in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.6 Sol leads 74.8 to 10.8.
- The biggest single-benchmark swing is ARC-AGI-1: 3.5% for GPT-4.1 mini and 97.5% for GPT-5.6 Sol.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $4 / $20 for GPT-5.6 Sol.
- GPT-5.6 Sol accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-4.1 mini | GPT-5.6 Sol | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 33.6 | 65.0 |
| Released | 2025-04-14 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 33K | 128K |
| Input $ / M tokens | $0.40 | $4 |
| Output $ / M tokens | $1.60 | $20 |
| Results tracked | 47 | 65 |
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Category by category
Coding GPT-5.6 Sol leads
GPT-4.1 mini: 30.6 (#293), GPT-5.6 Sol: 65.1 (#7)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| SciCode | 40.4% | 57.1% |
| WeirdML | 37.6% | 89.4% |
| LMArena Coding | 1367 | 1498 |
| DeepSWE | — | 72.7% |
| FrontierCode | — | 47.5% |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| CursorBench | — | 41.7% |
| LMArena WebDev | — | 1618 |
| FrontierSWE | — | 32.2% |
| GSO | — | 76.5% |
| BigCodeBench Instruct | 48.9% | — |
| MirrorCode | — | 20% |
| CadEval | 16% | — |
| ALE-Bench | — | 2,177 |
Agentic & Tool Use GPT-5.6 Sol leads
GPT-4.1 mini: 33.3 (#55), GPT-5.6 Sol: 50.3 (#7)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| APEX-Agents | — | 51.4% |
| Berkeley Function Calling Leaderboard | 50.5% | — |
| OSWorld 2.0 | — | 27.3% |
| τ²-bench Banking | — | 46.9% |
| PostTrainBench | — | 36.2% |
| BALROG | — | 60% |
| GBAEval | — | 52.6% |
| GDP.pdf | — | 30.7% |
| LMArena Search | — | 1257 |
| Vending-Bench 2 | — | 9,619 |
Reasoning GPT-5.6 Sol leads
GPT-4.1 mini: 10.8 (#340), GPT-5.6 Sol: 74.8 (#8)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| ARC-AGI-2 | 0% | 92.5% |
| Kagi LLM Benchmark | 48.6% | 67% |
| ARC-AGI-1 | 3.5% | 97.5% |
| CritPt | 0% | 32.3% |
| Chess Puzzles | 7% | 64% |
| LMArena Hard Prompts | 1349 | 1484 |
| Mystery Game Puzzles | 7% | 58% |
| DTBench | 68.8% | 96% |
| LMCA | 21.1% | 59.2% |
| Epoch Capabilities Index | 135.01 | 161.66 |
| SimpleBench | — | 71.7% |
| NYT Connections (extended) | — | 93.8% |
| EnigmaEval | — | 37.1% |
| EBR-Bench | — | 44.8% |
| Surface Evolver Bench | — | 93.1% |
| Bench to the Future 3 | — | 0.14 |
Math GPT-5.6 Sol leads
GPT-4.1 mini: 24.1 (#270), GPT-5.6 Sol: 85.6 (#9)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | 89.1% |
| OTIS Mock AIME 2024-2025 | 44.7% | 100% |
| LMArena Math | 1343 | 1474 |
| FrontierMath Tier 4 | — | 82.9% |
| ProofBench | — | 83% |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Erdős | — | 0% |
Knowledge GPT-5.6 Sol leads
GPT-4.1 mini: 34.7 (#194), GPT-5.6 Sol: 64.3 (#18)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| GPQA Diamond | 65.8% | 93.5% |
| SimpleQA Verified | 12.7% | 69.7% |
| LMArena Expert | 1338 | 1516 |
| MMLU-Pro | 78.3% | — |
| Vectara Hallucination Rate | — | 12.4% |
| GPQA (HELM) | 61.4% | — |
Multimodal GPT-5.6 Sol leads
GPT-4.1 mini: 35.8 (#82), GPT-5.6 Sol: 48.6 (#9)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| LMArena Vision | 1181 | 1281 |
| Blueprint-Bench 2 | — | 33.6% |
| Furniture Assembly | — | 56.7% |
| LMArena Document | — | 1483 |
Multilingual GPT-5.6 Sol leads
GPT-4.1 mini: 45.7 (#166), GPT-5.6 Sol: 55.3 (#32)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| LMArena Non-English | 1318 | 1452 |
| LMArena Chinese | 1329 | 1527 |
| LMArena French | 1358 | 1477 |
| LMArena German | 1351 | 1476 |
| LMArena Japanese | 1290 | 1471 |
| LMArena Korean | 1298 | 1442 |
| LMArena Russian | 1324 | 1468 |
| LMArena Spanish | 1319 | 1441 |
Instruction Following GPT-5.6 Sol leads
GPT-4.1 mini: 73.7 (#118), GPT-5.6 Sol: 77.7 (#16)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| LMArena Instruction Following | 1333 | 1482 |
| IFEval | 90.4% | — |
Long Context GPT-5.6 Sol leads
GPT-4.1 mini: 31.8 (#275), GPT-5.6 Sol: 45.4 (#42)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| LMArena Longer Query | 1344 | 1480 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference GPT-5.6 Sol leads
GPT-4.1 mini: 48.6 (#199), GPT-5.6 Sol: 73.3 (#12)
| Benchmark | GPT-4.1 mini | GPT-5.6 Sol |
|---|---|---|
| LMArena Text | 1340 | 1457 |
| LMArena Creative Writing | 1300 | 1448 |
| EQ-Bench Creative Writing | 1147 | 1972 |
| LMArena Multi-Turn | 1354 | 1460 |
| WildBench | 83.8% | — |
| EQ-Bench 4 | — | 1250 |
Frequently asked questions
Is GPT-4.1 mini better than GPT-5.6 Sol?
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 33.6 on the Noometry Index. GPT-4.1 mini costs 11× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 mini or GPT-5.6 Sol?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GPT-5.6 Sol lists at $4 and $20.
Is GPT-4.1 mini or GPT-5.6 Sol better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 65.1 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Sol does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 mini and GPT-5.6 Sol share?
34 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and GPT-5.6 Sol has 65.