Models / GPT-5.6 Sol Pro
GPT-5.6 Sol Pro
Mid-field among models available today on every use case measured so far.
- Price per million tokens
- $4.00 in · $20.00 out
Typical host on OpenRouter, 7 Oct 2026 · compare prices - Speed
- Not measured
- Intelligence Index
- Not measured
- Spring Prompt overall
- Not ranked yet
needs our benchmarks and two groups of results - Developer
- OpenAI, based in the US
Weights not published - Released
- Not recorded
1,050,000 tokens of context
Where it stands among the models you could choose
Ranked only among models available today (those you can call through OpenRouter), in the groups people choose between: the same price band, similar intelligence, the same speed, developers based in the same place. Retired models are left out.
| Among | Intelligence Index | Spring Prompt overall | Price | Speed |
|---|---|---|---|---|
| Models available today | – | – | 205th of 221Mistral Nemo | – |
| Models from developers based in the US | – | – | 87th of 103Llama 3.1 8B Instruct | – |
The name under each rank is the leader of that group. Price is the developer's list price (or the typical OpenRouter host where we haven't read one) for three input tokens to one output; intelligence and speed are from Artificial Analysis (data sourced from Artificial Analysis); "similar intelligence" means within 4 points on its Intelligence Index. Developer locations are where each company is based, not where a model is served. Groups under 3 models are not ranked.
How good is it, and for what?
Each use case ranks the available models its benchmarks measured, then those priced $3–10 per million tokens. The bar shows where it falls in that field, best to the right. Open a row for the results behind it.
Product listingsTurning a sparse product feed and photos into listings that can go live
- CatalogBench: has not measured this model.
Decks from an analysisTurning a finished analysis into a deck you could present as it is
- DeckBench: has not measured this model.
Marketing planningPlanning a year of ad spend without overspending
- ROASBench: has not measured this model.
Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls
- tau2-bench: has not measured this model.
- Berkeley Function Calling Leaderboard (BFCL) V4: has not measured this model.
- OpenHands Index: has not measured this model.
- Microsoft STATE-Bench: has not measured this model.
- Artificial Analysis: has not measured this model.
- Vending-Bench 2: has not measured this model.
Professional workReal tasks from banking, consulting and law, business documents and freelance projects
| Benchmark | GPT-5.6 Sol Pro | Rank among available | Best available |
|---|---|---|---|
| APEX-AgentsAPEX-Agents: tasks passed · reported | 51.4% | 20th of 37 | Claude Sonnet 5.5 75.5% |
- GDP.pdf: has not measured this model.
- Remote Labor Index: has not measured this model.
Reasoning and knowledgeHard questions across science, maths and general knowledge
- Artificial Analysis: has not measured this model.
WritingWhat people prefer in blind comparisons, and judged writing quality
- Arena (formerly LMArena): has not measured this model.
- UGI Leaderboard: has not measured this model.
Sticking to the factsSummarising without inventing things, and factual answers
- Vectara Hallucination Leaderboard: has not measured this model.
- Arena (formerly LMArena): has not measured this model.
- SimpleQA Verified (Epoch AI): has not measured this model.
Speed under pressureGood decisions against a real clock (fast chess)
- BulletBench: has not measured this model.
Against the alternatives
The models you would most likely weigh it against: the leaders of the groups above.
| GPT-5.6 Sol Pro | GPT-6.1 Sol leads overall | Claude Opus 5.5 near the top overall | GPT-6 Astra near the top overall | GPT-6 Sol near the top overall | |
|---|---|---|---|---|---|
| Price per million tokens | $8.00 | $4.00 | $8.00 | $20.00 | $4.00 |
| Tokens a second | – | 57 | 97 | 52 | – |
| Intelligence Index | – | 51.8 | 57.6 | 52.7 | 47.6 |
| Spring Prompt overall | – | 88 | 82 | 78 | 69 |
| Rank among available models, by use case | |||||
| Product listings | – | 2nd | 6th | 1st | 3rd |
| Decks from an analysis | – | 3rd | 5th | 1st | 2nd |
| Marketing planning | – | – | 5th | 1st | 2nd |
| Agents and tool use | – | 3rd | 2nd | 4th | 5th |
| Professional work | 22nd of 51 | 9th | 3rd | 5th | 13th |
| Reasoning and knowledge | – | 5th | 1st | 3rd | 11th |
| Writing | – | – | 4th | 17th | 40th |
| Sticking to the facts | – | 2nd | 6th | 27th | 51st |
| Speed under pressure | – | – | – | 14th | 10th |
Shaded figures are better than GPT-5.6 Sol Pro's. A dash means no result.
Where it has been measured
- APEX-Agents1 result
- BulletBenchNot measured
- CatalogBenchNot measured
- DeckBenchNot measured
- ROASBenchNot measured
- Arena (formerly LMArena)Not measured
- Artificial AnalysisNot measured
- Berkeley Function Calling Leaderboard (BFCL) V4Not measured
- GDP.pdfNot measured
- Microsoft STATE-BenchNot measured
- OpenHands IndexNot measured
- Remote Labor IndexNot measured
- SimpleQA Verified (Epoch AI)Not measured
- tau2-benchNot measured
- UGI LeaderboardNot measured
- Vectara Hallucination LeaderboardNot measured
- Vending-Bench 2Not measured
Every result
1 published results from 1 source, each in the source's own units, with the configuration that produced it.
APEX-Agents · reported by APEX-Agents · 1 result
| Measure | Value | Rank | Configuration | Dated |
|---|---|---|---|---|
| APEX-Agents: tasks passed% of tasks, higher is better | 51.4% | 21 of 39 | GPT-5.6 Sol Pro (max) | 1 Oct 2026 |
Not shown: Not your firm's documents or tools; graded by rubric, not by a client.