GPT-5.6 Sol
GPT-5.6 Sol is a chat-oriented large language model from OpenAI, positioned within the GPT-5 series and measured at roughly 64 output tokens per second in third-party benchmarking.
API Pricing
Cheapest on OpenRouter — 56% below avg| Provider | Input / 1M | Output / 1M | Cached / 1M |
|---|---|---|---|
| $1.00 | $5.00 | $0.100 | |
| $2.00 | $10.00 | $0.200 | |
| $2.00 | $10.00 | $0.200 | |
| $4.00 | $20.00 | $0.400 |
Prices updated daily. Last check: Aug 26, 2026
GPT-5.6 Sol pricing by provider
Input, output, and batch rates, plus alternatives, for one provider at a time.
Performance & Benchmarks
Source: Artificial Analysis →Reasoning & Knowledge
- GPQA Diamond94.1%
- Humanity's Last Exam49.5%
Coding
- SciCode56.1%
Agentic & Tool Use
- Terminal-Bench Hard65.9%
- Terminal-Bench v2.188.0%
- τ²-bench85.1%
- τ-bench Banking44.3%
Instruction & Long Context
- IFBench72.7%
- Long-Context Reasoning77.7%
Benchmarks measured Aug 2026. Scores are independent evaluations, not vendor-reported.
Model Details
General
- Creator
- OpenAI
- Modalities
- Text
Capabilities
- Tool Calling
- No
- Open Source
- No
Strengths & Limitations
Strengths
- Measured output throughput of about 63.8 tokens per second in Artificial Analysis benchmarking, a mid-range generation speed suitable for streamed chat responses
- Part of OpenAI's GPT-5 generation, so it can typically be swapped in behind the same API surface used for other GPT-5.x variants
- Chat-optimized, making it a direct fit for assistant, support, and conversational product surfaces without task-specific adaptation
- Independent third-party latency and throughput figures are available, which is not the case for every hosted model
- Benefits from OpenAI's broadly documented ecosystem of SDKs, client libraries, and integration tooling
- Streaming output partially offsets the initial first-token delay for user-facing interfaces
Limitations
- Time to first token of roughly 2,956 ms is high relative to lightweight chat models, which is noticeable in interactive UIs
- Throughput near 64 tokens per second is mid-range, so very long generations take proportionally longer to complete
- We do not track a confirmed context window for this entry — verify limits in OpenAI's documentation before planning long-document workloads
- Modality support (image or audio input) is not among the fields we have confirmed for this model
- Benchmark figures come from a single third-party source and can shift as providers tune their serving stacks
Key Features
About GPT-5.6 Sol
Common Use Cases
GPT-5.6 Sol fits chat and text-generation workloads where a few seconds of initial latency is acceptable in exchange for the response quality of a GPT-5 generation model: customer-facing assistants with streamed output, drafting and rewriting long-form content, summarizing documents, question answering over supplied context, and internal knowledge tools. The sub-three-second first-token figure makes it less appropriate for autocomplete, inline code suggestions, voice pipelines, or any interaction where users expect near-instant feedback; those cases are usually better served by a smaller, lower-latency sibling. For batch and offline jobs — bulk content generation, data enrichment, evaluation runs — the first-token delay is largely irrelevant and the ~64 tokens per second throughput becomes the figure that governs job duration. Before committing to it for high-volume production traffic, compare per-provider rates in the pricing table on this page against a lighter model in the same family.
Frequently Asked Questions
How much does GPT-5.6 Sol cost to use?
Pricing depends on which provider is serving the model and on the pricing type — input tokens, output tokens, cached input, and batch rates are usually billed differently. Because rates change frequently, check the live pricing table on this page for current figures across the providers we track.
What is GPT-5.6 Sol best used for?
It suits conversational assistants, long-form drafting and editing, summarization, and question answering over supplied text. Its measured time to first token of about 2.96 seconds makes it a weaker fit for autocomplete, voice, or other latency-critical interactive features.
How fast is GPT-5.6 Sol?
Artificial Analysis measures roughly 63.8 output tokens per second with a time to first token of about 2,956 milliseconds. That places generation speed in the mid range while initial response latency is on the slower side, so streaming output is worth enabling in user-facing applications.
What context window does GPT-5.6 Sol support?
We have not confirmed a context window figure for this entry in our database. Check OpenAI's official model documentation, or the documentation of whichever provider you are calling it through, for the authoritative input and output token limits.
Does GPT-5.6 Sol accept image input?
Input modality support is not among the fields we have verified for GPT-5.6 Sol, so we cannot confirm it either way. Refer to OpenAI's model reference for the definitive list of supported input types.
How does GPT-5.6 Sol compare to other GPT-5 variants?
It is one variant within OpenAI's GPT-5 generation, and the main tracked differentiators between siblings are throughput, first-token latency, and price. Compare its ~64 tokens per second and ~2.96 second first-token figures against other GPT-5.x entries in the catalog, then weigh those against the per-provider rates in the pricing table above.