Model comparison
GPT-4 Turbo vs GPT-5.6 Sol
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 30.5 on the Noometry Index.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. GPT-4 Turbo scores higher in 0 categories and GPT-5.6 Sol in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Sol leads 85.6 to 9.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.7% for GPT-4 Turbo and 100% for GPT-5.6 Sol.
- GPT-5.6 Sol is cheaper at $4 / $20 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
- GPT-5.6 Sol accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-4 Turbo | GPT-5.6 Sol | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 30.5 | 65.0 |
| Released | 2023-11-06 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 4K | 128K |
| Input $ / M tokens | $10 | $4 |
| Output $ / M tokens | $30 | $20 |
| Results tracked | 36 | 65 |
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Category by category
Coding GPT-5.6 Sol leads
GPT-4 Turbo: 33.8 (#249), GPT-5.6 Sol: 65.1 (#7)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| WeirdML | 18% | 89.4% |
| LMArena Coding | 1268 | 1498 |
| DeepSWE | — | 72.7% |
| FrontierCode | — | 47.5% |
| CursorBench | — | 41.7% |
| LMArena WebDev | — | 1618 |
| FrontierSWE | — | 32.2% |
| SciCode | — | 57.1% |
| GSO | — | 76.5% |
| BigCodeBench Instruct | 48.2% | — |
| MirrorCode | — | 20% |
| BigCodeBench Complete | 58.2% | — |
| ALE-Bench | — | 2,177 |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73.3% | — |
Agentic & Tool Use Not comparable
GPT-4 Turbo: —, GPT-5.6 Sol: 50.3 (#7)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| APEX-Agents | — | 51.4% |
| 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 |
| METR Time Horizons | 36.7% | — |
| Vending-Bench 2 | — | 9,619 |
Reasoning GPT-5.6 Sol leads
GPT-4 Turbo: 15.3 (#317), GPT-5.6 Sol: 74.8 (#8)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| SimpleBench | 25.1% | 71.7% |
| Chess Puzzles | 6% | 64% |
| LMArena Hard Prompts | 1251 | 1484 |
| DTBench | 61.6% | 96% |
| LMCA | 9.8% | 59.2% |
| Epoch Capabilities Index | 127.25 | 161.66 |
| ARC-AGI-2 | — | 92.5% |
| Kagi LLM Benchmark | — | 67% |
| NYT Connections (extended) | — | 93.8% |
| ARC-AGI-1 | — | 97.5% |
| CritPt | — | 32.3% |
| EnigmaEval | — | 37.1% |
| EBR-Bench | — | 44.8% |
| Mystery Game Puzzles | — | 58% |
| Surface Evolver Bench | — | 93.1% |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 59.4 | — |
Math GPT-5.6 Sol leads
GPT-4 Turbo: 9.0 (#322), GPT-5.6 Sol: 85.6 (#9)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0.7% | 89.1% |
| OTIS Mock AIME 2024-2025 | 6.7% | 100% |
| LMArena Math | 1272 | 1474 |
| FrontierMath Tier 4 | — | 82.9% |
| ProofBench | — | 83% |
| MATH Level 5 | 46.7% | — |
| FrontierMath Erdős | — | 0% |
Knowledge GPT-5.6 Sol leads
GPT-4 Turbo: 24.3 (#268), GPT-5.6 Sol: 64.3 (#18)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| GPQA Diamond | 46.6% | 93.5% |
| LMArena Expert | 1223 | 1516 |
| SimpleQA Verified | — | 69.7% |
| Confabulations | 28.4% | — |
| Vectara Hallucination Rate | — | 12.4% |
| MMLU | 81.3% | — |
Multimodal GPT-5.6 Sol leads
GPT-4 Turbo: 30.6 (#110), GPT-5.6 Sol: 48.6 (#9)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| LMArena Vision | 1090 | 1281 |
| Blueprint-Bench 2 | — | 33.6% |
| Furniture Assembly | — | 56.7% |
| LMArena Document | — | 1483 |
Multilingual GPT-5.6 Sol leads
GPT-4 Turbo: 40.5 (#216), GPT-5.6 Sol: 55.3 (#32)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| LMArena Non-English | 1245 | 1452 |
| LMArena Chinese | 1242 | 1527 |
| LMArena French | 1276 | 1477 |
| LMArena German | 1259 | 1476 |
| LMArena Japanese | 1194 | 1471 |
| LMArena Korean | 1187 | 1442 |
| LMArena Russian | 1259 | 1468 |
| LMArena Spanish | 1260 | 1441 |
Instruction Following GPT-5.6 Sol leads
GPT-4 Turbo: 65.8 (#216), GPT-5.6 Sol: 77.7 (#16)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| LMArena Instruction Following | 1249 | 1482 |
Long Context GPT-5.6 Sol leads
GPT-4 Turbo: 38.0 (#206), GPT-5.6 Sol: 45.4 (#42)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| LMArena Longer Query | 1254 | 1480 |
Writing & Preference GPT-5.6 Sol leads
GPT-4 Turbo: 47.7 (#206), GPT-5.6 Sol: 73.3 (#12)
| Benchmark | GPT-4 Turbo | GPT-5.6 Sol |
|---|---|---|
| LMArena Text | 1272 | 1457 |
| LMArena Creative Writing | 1269 | 1448 |
| LMArena Multi-Turn | 1267 | 1460 |
| EQ-Bench Creative Writing | — | 1972 |
| EQ-Bench 4 | — | 1250 |
Frequently asked questions
Is GPT-4 Turbo better than GPT-5.6 Sol?
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 30.5 on the Noometry Index.
Which is cheaper, GPT-4 Turbo or GPT-5.6 Sol?
GPT-5.6 Sol is cheaper. It lists at $4 per million input tokens and $20 per million output tokens; GPT-4 Turbo lists at $10 and $30.
Is GPT-4 Turbo or GPT-5.6 Sol better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 65.1 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Sol does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4 Turbo and GPT-5.6 Sol share?
27 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and GPT-5.6 Sol has 65.