GPT 5.6 Sol Economy
GPT-5.6 Sol is the flagship model in OpenAI’s GPT-5.6 series. It is specifically designed for complex reasoning, coding, and agentic workflows, and particularly excels at multi-step problem solving, command-line assistance, and high-quality software tasks. This model is recommended when output quality and reliability matter more than raw throughput.
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GPT 6 Astra Economy
GPT-6 Astra is OpenAI's flagship frontier model engineered for long-horizon, complex end-to-end enterprise workflows. Representing a major generational leap toward agentic intelligence, Astra integrates deep multi-step reasoning, advanced software engineering, and native computer-use capabilities to navigate software interfaces and execute multi-application workflows directly via GUI. Powered by symbolic world modeling and dynamic course-correction, it can break open-ended goals into actionable steps, handle ambiguous edge cases, and execute complex operations across unstructured environments. Setting new benchmarks on ARC-AGI-3 as well as complex financial, scientific, and coding tasks, GPT-6 Astra is built for enterprise agent orchestration, autonomous software development, financial intelligence, and complex legal/business decision support.
GPT 5.5 Economy
GPT-5.5 is a frontier model released by OpenAI on April 23, 2026. It features a context window of over 1 million tokens—922,000 input tokens and 128,000 output tokens—and supports both text and image inputs. The model scores 88.7% on SWE-bench Verified and 92.4% on MMLU, while reducing hallucinations by 60% compared with GPT-5.4. It excels in agentic coding, computer use, and deep research, while maintaining per-token latency comparable to GPT-5.4.
GPT 5.6 Terra Economy
GPT-5.6 Terra is the balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is well suited for everyday coding, reasoning, and agentic workflows, offering a strong balance of quality, latency, and cost for general production use.
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GPT 5.6 Sol API
GPT-5.6 Sol is OpenAI's flagship reasoning model for complex professional work across coding, research, science, cybersecurity, computer use, and design. It is the highest-capability tier in the GPT-5.6 family, built to complete demanding workflows with stronger token efficiency and more deliberate tool use.
On iCreat, you can call gpt-5.6-sol through an OpenAI-compatible Chat Completions API. The model supports text and image input, streamed responses, and configurable reasoning, giving existing OpenAI SDK applications a direct path from Playground evaluation to production integration.
Model Positioning
Sol is the flagship capability tier in OpenAI's new Sol, Terra, and Luna model family. Choose it for the hardest requests where completion quality, professional judgment, and sustained execution matter more than minimum latency. Terra targets a balance of intelligence and cost, while Luna is designed for efficient high-volume traffic.
GPT-5.6 Sol combines a 1.05M-token context window with a 922K-token maximum input and 128K-token maximum output. It supports six reasoning-effort levels from none through max, allowing one model to cover fast direct responses and quality-first analysis.
Key Capabilities
Complex Coding and Agent Work
GPT-5.6 Sol is designed for long-horizon software engineering that requires planning, repository inspection, implementation, testing, and correction. With application-provided tools and permissions, it can coordinate multi-step work instead of stopping at isolated code generation.
Professional Knowledge Work
The model can synthesize messy context from documents, business systems, research sources, and ongoing workflows into structured, review-ready outputs. OpenAI emphasizes financial, legal, consulting, scientific, and other expert-level tasks where evidence and execution both matter.
Reasoning from None to Max
Reasoning effort supports none, low, medium, high, xhigh, and max, with medium as the official default. Lower settings provide a latency baseline; max is reserved for the hardest tasks that benefit from additional exploration and verification.
Visual and Design Judgment
GPT-5.6 Sol accepts text and image input and can preserve original image dimensions at supported detail settings. Its visual understanding and frontend-design improvements are useful for inspecting interfaces, following visual references, and refining the hierarchy and usability of generated experiences.
Tool-Oriented Production Work
OpenAI's GPT-5.6 platform adds Programmatic Tool Calling, persisted reasoning, explicit cache breakpoints, and beta multi-agent execution through the Responses API. On iCreat, the documented integration uses the OpenAI-compatible Chat Completions interface; applications still provide the actual tools, state, and authorization.
Pricing
| Token Type | Price |
|---|---|
| Input | $0.50 per 1M tokens |
| Output | $3.00 per 1M tokens |
| Cache Read | $0.05 per 1M tokens |
| Cache Write | $0.625 per 1M tokens |
Use Cases
- Production coding Agents: plan, implement, test, and review changes across large repositories through a controlled tool harness.
- Professional research: combine extensive source material with browsing or retrieval evidence to produce decision-ready analysis.
- Visual interface development: interpret screenshots and references, build frontend experiences, and inspect rendered results with appropriate visual tools.
- Document and business workflows: turn reports, files, and operational context into polished plans, analyses, presentations, or structured outputs.
- Science and cybersecurity: support difficult technical investigation and analysis within appropriate access, safety, and human-review boundaries.
Applications must still define tool access, approval boundaries, validation rules, and stopping conditions before the model can act on files, systems, or external services.
Model Comparison
GPT-5.6 Sol vs GPT-5.5
| Factor | GPT-5.6 Sol | GPT-5.5 |
|---|---|---|
| Positioning | GPT-5.6 flagship for complex professional work | Previous frontier model for coding and professional work |
| Context Window | 1.05M tokens | 1.05M tokens |
| Maximum Output | 128K tokens | 128K tokens |
| Knowledge Cutoff | February 16, 2026 | December 1, 2025 |
| Reasoning Control | none, low, medium, high, xhigh, max; optional Pro mode |
none, low, medium, high, xhigh |
| Core Difference | Adds Max effort, Pro mode, stronger token efficiency, design judgment, and new tool orchestration options | Established GPT frontier baseline without GPT-5.6-specific controls |
| Best Fit | New quality-first production Agents and complex multimodal work | Existing GPT-5.5 workflows that have not yet been evaluated for migration |
GPT-5.6 Sol vs Claude Fable 5 and Gemini 3.1 Pro Preview
| Factor | GPT-5.6 Sol | Claude Fable 5 | Gemini 3.1 Pro Preview |
|---|---|---|---|
| Positioning | Frontier model for complex professional work | Highest-capability widely released Claude model for demanding reasoning and long-horizon Agents | Advanced Gemini reasoning model for complex multimodal and agentic work |
| Context Window | 1.05M tokens | 1M tokens | 1,048,576 tokens |
| Maximum Output | 128K tokens | 128K tokens | 65,536 tokens |
| Official Input Modalities | Text and image | Text and image | Text, image, video, audio, and PDF |
| Reasoning Control | none, low, medium, high, xhigh, max; optional Pro mode |
Always-on Adaptive Thinking with effort control | Dynamic thinking with low, medium, high; default high |
| Core Difference | Fine-grained reasoning, broad tool stack, computer use, and design judgment | Quality-first long-running Agents with always-on Adaptive Thinking | Broad native multimodal input and Google ecosystem integration |
| Best Fit | OpenAI-based coding, research, visual design, and production Agents | Multi-stage autonomous work where Claude continuity is central | Multimodal analysis across video, audio, PDFs, and long documents |
Why Choose GPT-5.6 Sol?
Choose GPT-5.6 Sol when the application needs OpenAI's highest-capability GPT-5.6 tier and must handle more than a single answer. Its combination of long context, multimodal input, six reasoning-effort levels, visual judgment, and tool-oriented behavior makes it a strong foundation for complex production workflows.
iCreat provides that model through a familiar OpenAI-compatible endpoint. Teams can test representative prompts and images in the Playground, then use the same model ID for streamed applications without managing model infrastructure.
Specifications
| Category | Description |
|---|---|
| Model Name | GPT-5.6 Sol |
| Provider | OpenAI |
| Model ID | gpt-5.6-sol |
| Official Snapshot ID | gpt-5.6-sol |
| Release Date | July 9, 2026 |
| Model Type | Frontier reasoning LLM |
| Context Window | 1,050,000 tokens |
| Maximum Input | 922,000 tokens |
| Maximum Output | 128,000 tokens |
| Knowledge Cutoff | February 16, 2026 |
| Official Input Modalities | Text and image |
| Output Modalities | Text |
| Official Reasoning Control | none, low, medium, high, xhigh, max; optional Pro mode |
| Default Effort | medium |
| iCreat Input Modalities | Text and image |
| iCreat API Features | OpenAI-compatible Chat Completions API, streaming, thinking and reasoning-effort configuration |
| Best Suited For | Complex coding, professional research, visual design, science, cybersecurity, tool-driven Agents |
Architecture
OpenAI has not published GPT-5.6 Sol's parameter count, expert configuration, layer count, or underlying network topology. It should therefore be described as a frontier reasoning model rather than assigned an unverified dense or Mixture-of-Experts architecture.
At the product level, the model separates reasoning effort from the visible text response and can use internal reasoning tokens before producing an answer. Pro mode is an execution mode that applies more model work to the same GPT-5.6 model; it is not evidence of a separate architecture or a separate model slug.
Production Notes
Start with medium as the official reasoning default, then compare one level lower and one level higher on representative tasks. Use max only when measured quality gains justify the additional latency and token use.
Treat the context window as a shared envelope. The published maximum input is lower than the full context limit because space must remain for reasoning and output; also reserve room for system instructions, tool definitions, conversation state, and retrieved evidence.
For image-heavy workflows, original or automatic detail can preserve large image dimensions and increase input tokens and latency. Set image detail intentionally and keep full resolution only when OCR, localization, or visual inspection requires it.
OpenAI Responses API features such as Pro mode, Programmatic Tool Calling, persisted reasoning, and beta multi-agent use request shapes beyond the Chat Completions examples on this iCreat page. Implement only the fields supported by the endpoint you are calling.
FAQ
Is gpt-5.6 a different model from GPT-5.6 Sol?
No. OpenAI states that the gpt-5.6 alias routes to gpt-5.6-sol. Using the explicit gpt-5.6-sol ID makes the intended capability tier clear.
Should an existing GPT-5.5 prompt be rewritten before testing GPT-5.6 Sol?
Usually not. Start with the working prompt and the same reasoning setting, then test the same setting and one level lower on representative tasks. Change the prompt only when evaluation reveals a specific failure.
Can GPT-5.6 Sol be fine-tuned?
No. OpenAI's current model page lists fine-tuning as unsupported. Adapt behavior through prompts, reasoning effort, tools, retrieval, structured outputs, and application-level evaluation.
Do OpenAI account rate limits determine the limits of this iCreat endpoint?
No. OpenAI's native API tiers and iCreat are separate services. Use the limits, availability, and error responses shown by the iCreat account and endpoint when planning concurrency and retries.