GPT-4o vs GPT-5.6 Sol Pro
GPT-4o costs 2.0x less per output token than GPT-5.6 Sol Pro ($10.00 vs $20.00 per million). Updated October 21, 2026; 2 benchmarks have a result for both.
GPT-4o or GPT-5.6 Sol Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o for output tokens 2.0x cheaper ($10.00 vs $20.00 per million) and work measured by DTBench or LMCA, where it leads.
- Shared results
- 2
- GPT-4o only
- 25
- GPT-5.6 Sol Pro only
- 5
- Like-for-like categories
- 1 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Web design
Design Arena: websites
No call
Only GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
GPT-5.6 Sol Pro
GPT-5.6 Sol Pro takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o
GPT-4o $0.0075, GPT-5.6 Sol Pro $0.014 per turn.
List prices
At a glance
- Coding index
- GPT-4o not benchmarked, GPT-5.6 Sol Pro not benchmarked.
- Widest category
- General, 37.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMCA: GPT-4o 16.6% against GPT-5.6 Sol Pro 59.2%, 42.6 points apart on a 0 to 100 scale.
- Output price
- GPT-4o $10.00 against GPT-5.6 Sol Pro $20.00 per million output tokens, 2.0x apart.
- Context window
- GPT-4o takes 128K tokens, GPT-5.6 Sol Pro 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-4o | Bars | GPT-5.6 Sol Pro | Ties |
|---|---|---|---|---|
| General | 0 | 2 | ||
| All shared boards | 0 | 2 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| SWE-bench Verified | 38.8% | Not measured | Only GPT-4o measured |
| SWE-bench Lite | 38.0% | Not measured | Only GPT-4o measured |
| SWE-bench (full test set) | 18.8% | Not measured | Only GPT-4o measured |
| SWE-bench Multimodal | 30.4% | Not measured | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | 30.9% | Not measured | Only GPT-4o measured |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | Not measured | Only GPT-4o measured |
| WeirdML | Not measured | 89.4% | Only GPT-5.6 Sol Pro measured |
| SciCode | 1.5% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| Neither model has a result on 2 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 25.1% | Not measured | Only GPT-4o measured |
| APEX-Agents | Not measured | 51.4% | Only GPT-5.6 Sol Pro measured |
| GDPval | 9.9% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 54.3% | Not measured | Only GPT-4o measured |
| Humanity's Last Exam (Artificial Analysis run) | 2.4% | Not measured | Only GPT-4o measured |
| ARC-AGI | 4.5% | Not measured | Only GPT-4o measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o measured |
| SimpleBench | Not measured | 71.7% | Only GPT-5.6 Sol Pro measured |
| Chess puzzles | Not measured | 68.0% | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| AA Math Index | 6.0 | Not measured | Only GPT-4o measured |
| AIME 2025 (Artificial Analysis run) | 6.0% | Not measured | Only GPT-4o measured |
| FrontierMath, tier 4 | Not measured | 80.5% | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 74.8% | Not measured | Only GPT-4o measured |
| MMLU | 88.1% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 831 | Not measured | Only GPT-4o measured |
| Design Arena: UI components | 885 | Not measured | Only GPT-4o measured |
| Design Arena: game dev | 906 | Not measured | Only GPT-4o measured |
| Design Arena: data viz | 858 | Not measured | Only GPT-4o measured |
| Design Arena: 3D | 869 | Not measured | Only GPT-4o measured |
| Design Arena: all code categories | 861 | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| IFBench | 34.3% | Not measured | Only GPT-4o measured |
| Long context reasoning (AA-LCR) | 49.3% | Not measured | Only GPT-4o measured |
| DTBench | 64.5% | 96.0% | GPT-5.6 Sol Pro |
| LMCA | 16.6% | 59.2% | GPT-5.6 Sol Pro |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GPT-4o costs less
Repository review
50K input + 3K output tokens
GPT-4o costs less
Agent loop
200K input + 10K output tokens
GPT-4o costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-4o | OpenAI GPT-5.6 Sol Pro |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | May 13, 2024 | July 9, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $2.50 | $4.00 |
| Output $/Mtok | $10.00 | $20.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o better than GPT-5.6 Sol Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o for output tokens 2.0x cheaper ($10.00 vs $20.00 per million) and work measured by DTBench or LMCA, where it leads.
Which is cheaper, GPT-4o or GPT-5.6 Sol Pro?
GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens; GPT-5.6 Sol Pro costs $4.00 and $20.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o or GPT-5.6 Sol Pro?
GPT-5.6 Sol Pro, with 1.05M tokens against 128K.
How many benchmarks is the GPT-4o vs GPT-5.6 Sol Pro comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. GPT-4o's coding index rests on 0 independent benchmarks and GPT-5.6 Sol Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.