GPT-5.6 Sol Review 2026: OpenAI’s Coding and Reasoning Model
GPT-5.6 Sol is OpenAI's flagship coding and reasoning model, scoring state-of-the-art on the Artificial Analysis Coding Agent Index. Covers pricing, benchmarks, and who should use it in 2026.
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GPT-5.6 Sol: Setting the New State of the Art in Coding Benchmarks
GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, released July 9, 2026, sitting above GPT-5.6 Terra and GPT-5.6 Luna in capability and price. It is OpenAI's best coding model to date, setting a new state of the art on the Artificial Analysis Coding Agent Index at a score of 80 -- 2.8 points above Fable 5 -- while using less than half the output tokens, less than half the time, and costing roughly a third less. For engineering and research teams deciding which frontier model to standardise on, Sol is the model built for the hardest coding, cybersecurity, and long-horizon agentic work.
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Overall Rating 4.7/5 Best For Engineering and security teams running the hardest coding, cybersecurity, and long-horizon agentic workloads Pricing $4 per million input tokens, $20 per million output tokens (promotional pricing through at least November 21, 2026); cache writes at 1.25x the uncached rate Free Plan No -- API access only, also available via ChatGPT Pro/Plus model selection Ease of Use 4.4/5 Business Value 4.8/5
What Is GPT-5.6 Sol and Why Does It Matter?
GPT-5.6 Sol is OpenAI's answer to the question of how far a coding-and-reasoning model can go before cost becomes the limiting factor. It roughly corresponds to the unsuffixed flagship tier used in earlier GPT-5 families, and the gpt-5.6 API alias routes requests to it by default. On the Artificial Analysis Coding Agent Index, Sol sets a new state of the art at 80 -- 2.8 points above Claude Fable 5.1 -- while using less than half the output tokens, less than half the time, and costing about a third less to reach that score. For teams comparing it against GPT-5.6 Terra or GPT-5.6 Luna, Sol is the tier built specifically for the hardest, most demanding tasks in the family.
Who Should Use GPT-5.6 Sol?
- Engineering teams running agentic coding: Sol's state-of-the-art Coding Agent Index score and lower token/time cost make it the default pick for production coding agents and large refactors.
- Security researchers: Strong ExploitBench and ExploitGym results make Sol a credible choice for long-horizon vulnerability research and exploitation workflows.
- Finance and consulting teams: Model ML reported Sol produced more polished, accurate decks using 39% fewer tokens per deck across its FinBench evaluation and 20 client workflows.
- Biology and life-sciences researchers: On GeneBench v1, Sol achieves stronger results than GPT-5.5 on long-horizon genomics and quantitative-biology analysis while using fewer tokens.
Professional reality: Sol is the most expensive model in the GPT-5.6 family. Teams running high-volume, lower-complexity workloads should check whether Terra or Luna already meets their quality bar before paying Sol's premium.
GPT-5.6 Sol Features That Drive Results
State-of-the-Art Coding Agent Performance
Sol scores 80 on the Artificial Analysis Coding Agent Index, 2.8 points above Claude Fable 5.1, while using less than half the output tokens and time and costing about a third less to reach that score.
Business outcome: production coding agents complete more work per dollar without sacrificing output quality.
Strong Long-Horizon Security Research
On ExploitBench, Sol is competitive with Mythos Preview using only about a third of the output tokens. On ExploitGym, a UC Berkeley-built benchmark, Sol demonstrates strong vulnerability research and exploitation capability.
Business outcome: security teams get frontier-level research assistance at materially lower token cost per task.
Adjustable Reasoning Effort
Sol supports reasoning effort levels of none, low, medium (the default), high, xhigh, and max, letting teams trade latency and cost against reasoning depth per request.
Business outcome: teams tune compute spend to task difficulty instead of paying max-effort pricing on every call.
Verified Gains on Real Client Workflows
Model ML's Chaz Englander reported Sol is the first model that consistently generates client-ready decks, using 39% fewer tokens per deck than Fable while producing clearer, more accurate visualizations across 20 challenging workflows and hundreds of decks in its FinBench evaluation.
Business outcome: fewer revision cycles and lower token spend on client-facing analytical output.
Text and Image Input
Sol accepts text and image input with text-only output; audio is not supported. Prompts over 272K input tokens are priced at 2x input and 1.5x output for the full request.
Business outcome: covers the large majority of document- and screenshot-based coding and analysis workflows without a separate vision model.
Stronger Genomics and Quantitative-Biology Results
On GeneBench v1, which evaluates long-horizon genomics and quantitative-biology analyses, Sol achieves stronger results than GPT-5.5 while using fewer tokens.
Business outcome: life-sciences teams get improved analytical accuracy without a proportional increase in compute spend.
GPT-5.6 Sol Pricing in 2026
GPT-5.6 Sol costs $4 per million input tokens and $20 per million output tokens -- a 20% reduction on input and a 33% reduction on output versus its original preview pricing of $5/$30. This promotional pricing is confirmed available through at least November 21, 2026. Prompts with more than 272K input tokens are priced at 2x the input rate and 1.5x the output rate for the full request. Cache writes are billed at 1.25x the uncached input token rate.
| Plan | Price | What You Get |
|---|---|---|
| API Access Best Value | $4 per million input tokens; $20 per million output tokens | Promotional pricing confirmed through at least November 21, 2026. Standard image input, text-only output. |
| Extended context (>272K tokens) | 2x input rate; 1.5x output rate | Applies to the full request once input exceeds 272K tokens. |
| Cache writes | 1.25x the uncached input rate | Standard OpenAI prompt-caching mechanics apply. |
| ChatGPT Pro / Plus | Included in subscription | Sol is selectable as a model option for Pro and Plus users within ChatGPT; GPT-5.6 Sol Pro remains the dedicated Pro-tier option. |
Visit the official GPT-5.6 Sol model page to check the latest pricing and plans.
Where GPT-5.6 Sol Is Strong / Where It Needs Care
- Best-in-class coding agent performanceState-of-the-art 80 on the Artificial Analysis Coding Agent Index, beating Claude Fable 5.1 while using less than half the tokens and time.
- Verified real-world efficiency gainsModel ML's independent evaluation found 39% fewer tokens per deck with more accurate output versus Fable.
- Strong security and biology performanceCompetitive ExploitBench/ExploitGym results and GeneBench v1 gains over GPT-5.5 extend its strength beyond coding alone.
- Flexible reasoning-effort controlSix effort levels from none to max let teams tune cost against reasoning depth per call.
- Most expensive model in its familyAt $4/$20 per million tokens, Sol costs 4x Terra's $1/$6-equivalent tier and far more than Luna for teams that don't need flagship-level reasoning.
- Audio input not supportedTeams needing native audio input must route that modality through a different model.
- Long-context prompts carry a price premiumPrompts over 272K input tokens are billed at 2x input and 1.5x output for the entire request, not just the overflow portion.
- Professional RealityGPT-6.1 Sol and GPT-6 Astra now sit above GPT-5.6 Sol in OpenAI's lineup -- teams starting fresh in late 2026 should confirm whether Sol or a newer tier better fits their budget and performance needs.
Real-World Use Cases
Production Coding Agents and Large Refactors
Engineering teams running autonomous coding agents get state-of-the-art benchmark performance at under half the token and time cost of comparable models, making large-scale refactors and multi-step coding tasks more economical to automate.
Vulnerability Research and Exploitation
Security teams get competitive ExploitBench and ExploitGym performance for long-horizon vulnerability research, using roughly a third of the output tokens needed by comparable models.
Client-Facing Financial Analysis and Decks
Model ML's deployment across 20 client workflows and its FinBench evaluation shows Sol produces more polished, accurate decks with fewer revision cycles than prior-generation models.
Genomics and Quantitative Biology Research
Life-sciences teams running long-horizon genomics analysis on GeneBench v1-style workloads get stronger results than GPT-5.5 while consuming fewer tokens per task.
How to Get Started With GPT-5.6 Sol
Access Sol via the OpenAI API using the gpt-5.6 alias, or select it directly in ChatGPT Pro/Plus model selection.
Set reasoning.effort deliberately -- start at medium (the default) and only raise to high, xhigh, or max where task difficulty genuinely requires it.
Watch the 272K input-token threshold -- prompts above it are billed at 2x input and 1.5x output for the whole request, so chunk very large inputs where possible.
Benchmark against Terra or Luna on a representative task before committing production volume to Sol's premium pricing.
Is GPT-5.6 Sol Worth It in 2026?
For teams running the hardest coding, security, or long-horizon agentic workloads, GPT-5.6 Sol is worth the premium -- its state-of-the-art Coding Agent Index score comes with lower token and time cost than rival flagship models, not just better raw accuracy. The verified Model ML case study adds real-world evidence beyond OpenAI's own benchmarks. The main caveat is cost: at $4/$20 per million tokens, Sol is priced well above Terra and Luna, so teams should confirm their workload genuinely needs flagship-tier reasoning before routing high volume through it. Teams should also note that GPT-6.1 Sol and GPT-6 Astra now sit above this model in OpenAI's lineup, so Sol's relative position will keep shifting as the GPT-6 family matures.
GPT-5.6 Sol vs the Competition
| Decision Area | GPT-5.6 Sol | When Another Option Wins |
|---|---|---|
| Best for | The hardest coding, cybersecurity, and long-horizon agentic workloads | GPT-5.6 Terra for mid-tier workloads that don't need flagship reasoning |
| Pricing | $4 input / $20 output per million tokens | GPT-5.6 Luna for high-volume, cost-sensitive workloads |
| Key feature | State-of-the-art 80 on the Artificial Analysis Coding Agent Index | Claude Fable 5.1 for teams already standardised on Anthropic's tooling |
| Scaling | Six reasoning-effort levels let teams tune cost against task difficulty | GPT-6 Astra for teams needing OpenAI's newest flagship tier |
GPT-5.6 Sol vs Claude Fable 5.1
Sol scores 80 on the Artificial Analysis Coding Agent Index versus Fable 5.1's lower score, while using less than half the output tokens and time and costing roughly a third less to get there. Model ML's independent FinBench evaluation found Sol used 39% fewer tokens per deck than Fable while producing more accurate output.
Choose GPT-5.6 Sol if: Coding agent performance and token efficiency are the deciding factors Choose Claude Fable 5.1 if: Your team's tooling and evaluation baselines are already built around Anthropic's model behaviour
GPT-5.6 Sol vs GPT-5.6 Terra and Luna
Sol is the flagship of the GPT-5.6 family, with Terra positioned as the mid-tier model and Luna as the cheapest, highest-volume option. All three share the same reasoning-effort architecture and strong ExploitGym results, but Sol leads on raw coding and reasoning capability while costing the most per token.
Choose GPT-5.6 Sol if: Your workload needs the family's highest reasoning ceiling Choose Terra or Luna if: Your workload is high-volume or cost-sensitive and doesn't need flagship-tier reasoning
Frequently Asked Questions
Is GPT-5.6 Sol free to use in 2026?
No. Sol is a paid API model at $4 per million input tokens and $20 per million output tokens, with promotional pricing confirmed through at least November 21, 2026. It is also selectable within ChatGPT Pro and Plus subscriptions, and GPT-5.6 Sol Pro remains the dedicated Pro-tier option.
What is GPT-5.6 Sol best used for?
It is best used for the hardest coding, cybersecurity, and long-horizon agentic workloads. It sets a new state of the art on the Artificial Analysis Coding Agent Index, performs competitively on security benchmarks like ExploitBench and ExploitGym, and shows verified gains in real client financial-analysis workflows via Model ML's evaluation.
How does GPT-5.6 Sol compare to GPT-5.6 Terra and Luna?
Sol is the flagship of the family, Terra is the mid-tier option, and Luna is the cheapest, highest-volume option. Sol leads on raw reasoning and coding benchmark performance but costs significantly more per token than either sibling model.
Is GPT-5.6 Sol worth it for small businesses?
For small teams doing substantial coding or security work, Sol's efficiency gains (fewer tokens and less time per completed task) can offset its higher per-token price. Teams with lighter, high-volume workloads should check GPT-5.6 Luna first, since Sol's premium is hardest to justify at low task complexity.
What are the main limitations of GPT-5.6 Sol?
Sol is the most expensive model in its family, does not support audio input, and applies a price premium (2x input, 1.5x output) to the full request once input exceeds 272K tokens. OpenAI has also since released GPT-6.1 Sol and GPT-6 Astra above it in the lineup, so its relative position continues to shift.
Key Takeaways
- GPT-5.6 Sol is best for engineering, security, and research teams running the hardest coding and long-horizon agentic workloads who need frontier-level reasoning
- Pricing is $4 per million input tokens and $20 per million output tokens, with promotional pricing confirmed through at least November 21, 2026 -- no free plan, but included in ChatGPT Pro/Plus model selection
- Biggest strength is state-of-the-art coding agent performance verified by both OpenAI's own benchmarks and Model ML's independent client-workflow evaluation -- main limitation is premium pricing relative to the rest of the GPT-5.6 family
Best GPT-5.6 Sol Alternatives
- GPT-5.6 Terra -- The mid-tier sibling for workloads that don't need flagship-level reasoning at Sol's premium price.
- GPT-5.6 Luna -- The cheapest option in the family for high-volume, cost-sensitive AI workloads.
- Claude Fable 5.1 -- A strong alternative for teams already standardised on Anthropic's tooling and evaluation baselines.
- GPT-6 Astra -- OpenAI's newer flagship for teams wanting the most current model generation.
Bottom Line: GPT-5.6 Sol earns its premium price with genuinely state-of-the-art coding agent performance, verified real-world efficiency gains, and strong security and biology results -- it's the right choice for the hardest workloads, but Terra or Luna should be checked first for anything less demanding.
Last Reviewed: October 2026 | Reviewed by theaitoolsbox.com editorial team
Quick Answers
What does GPT-5.6 Sol cost?
GPT-5.6 Sol costs $4 per million input tokens and $20 per million output tokens, with promotional pricing confirmed through at least November 21, 2026.
Who is GPT-5.6 Sol best for?
GPT-5.6 Sol is best for engineering teams running high-volume production workloads that need cost-efficient reasoning and easier auditability.
How easy is GPT-5.6 Sol to use?
GPT-5.6 Sol has an ease-of-use rating of 4.5/5 based on our testing.
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