Repository-scale coding
Engineering work that benefits from a large context window, code execution tools, patch application and sustained reasoning across many files.
Independent tool overview
GPT-6 Sol: a faster model for complex coding and agents
GPT-6 Sol is OpenAI's reasoning model for complex coding and agentic workflows, positioned below GPT-6 Astra with lower latency and API cost.
Visit the official GPT-6 Sol site ↗
- Best for
- Complex coding and agentic workflows
- Standard API price
- $2 input / $10 output per 1M tokens
- Context and output
- 1.05M context / 128K maximum output
- API model ID
- gpt-6-sol
- Default reasoning
- Medium
Overview
What GPT-6 Sol is
GPT-6 Sol is designed for complex coding and agentic workflows that still need strong reasoning but do not require OpenAI's highest-priced GPT-6 Astra tier. OpenAI introduced Sol and Luna as faster, more affordable GPT-6 models for work at scale, with Sol occupying the more capable of the two new tiers.
The model accepts text and image inputs and produces text output. Its 1,050,000-token context window and 128,000-token maximum output support large repositories, long documents and multi-step agent runs, while selectable reasoning effort lets teams trade response time and token use against additional deliberation.
GPT-6 Sol is available through the Responses API under the model ID gpt-6-sol. The Responses API is the fuller integration path because it supports OpenAI's built-in tools alongside function calling; Chat Completions limits function calling to requests using no reasoning effort.
Use cases
Who GPT-6 Sol is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Tool-using agents
Agents that need to search the web or files, call functions, use MCP servers, operate computers and coordinate multi-step workflows.
Long-document analysis
Technical specifications, research packets and business documents that exceed the comfortable context range of smaller models.
Scaled professional automation
Production workloads that need stronger reasoning than a budget model while keeping cost below the GPT-6 Astra tier.
Capabilities
Core GPT-6 Sol features
Six reasoning-effort levels
Supports none, low, medium, high, xhigh and max reasoning effort, with medium as the documented default.
1.05M-token context window
Processes up to 1,050,000 tokens of context and can return as many as 128,000 output tokens in a response.
Text and image understanding
Accepts text and image inputs for workflows that combine written instructions, screenshots, diagrams or other visual material.
Broad Responses API tool support
Supports web search, file search, image generation, code interpreter, hosted shell, apply patch, skills, computer use, MCP and tool search.
Structured output and function calling
Can stream responses, call functions and return structured outputs for integration into software and automation pipelines.
Multiple processing tiers
Standard processing can be supplemented with half-price Batch or Flex processing and faster processing at twice the applicable token rates.
Efficient prompt caching
Cached input is priced at 10% of normal input, while explicit cache writes are billed at 1.25 times the uncached input rate.
Process
How the GPT-6 Sol workflow works
Step 1
Choose Sol for the workload
Use it when the task needs substantial reasoning, long context or multiple tools but does not justify GPT-6 Astra's higher rate.
Step 2
Build on the Responses API
Send requests to gpt-6-sol through the Responses API when built-in tools, reasoning controls and function calling are part of the design.
Step 3
Set reasoning effort deliberately
Begin with the medium default, then evaluate lower settings for latency-sensitive work or higher settings for difficult coding and planning tasks.
Step 4
Arrange prompts for caching
Keep stable instructions and reusable context at the beginning of requests so repeated prefixes can benefit from discounted cached input.
Step 5
Evaluate quality, latency and cost
Measure the model against representative tasks before selecting processing tiers or routing only the hardest requests to Astra.
Cost
GPT-6 Sol pricing and free plan
GPT-6 Sol uses token-based API pricing. The standard short-context rate is $2 per million input tokens and $10 per million output tokens. Requests above 272K input tokens receive higher long-context rates for the full request.
Standard processing
$2 input / $10 output per 1M tokens
The default API processing tier for short-context requests.
- $0.20 per 1M cached input tokens
- $2.50 per 1M cache-write tokens
- Long-context pricing applies when input exceeds 272K tokens
Batch and Flex
50% of Standard rates
Lower-cost processing for workloads that can accept asynchronous or flexible scheduling.
- Useful for offline evaluations and bulk jobs
- Long-context multipliers still apply
- Confirm the processing mode fits the workload's latency requirements
Fast mode
2× the applicable rates
Higher-priced processing intended for workloads that prioritize faster responses.
- Standard short-context equivalent is $4 input / $20 output
- Regional processing can add a 10% premium
- EU data residency is available only with Standard processing
Pricing checked . Check current pricing at the source ↗
Assessment
GPT-6 Sol strengths and limitations
Where it stands out
- Combines a very large context window with OpenAI's broadest agent-tool surface.
- Costs one-fifth of GPT-6 Astra's documented standard token rates for short-context requests.
- Supports fine-grained reasoning control from none through max.
- Fits both interactive development and lower-cost asynchronous processing tiers.
What to consider
- OpenAI positions GPT-6 Astra, not Sol, as its most capable model for the hardest end-to-end work.
- Inputs above 272K tokens cost more for the entire request, so the maximum context window should not be treated as a flat-price allowance.
- Audio and video input are not supported by the documented model interface.
- Fine-tuning is not supported.
- Chat Completions function calling is documented only when reasoning effort is set to none; use the Responses API for the fuller tool experience.
Compare
GPT-6 Sol alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Consumer
GPT-6 Astra
Choose GPT-6 Astra when maximum reasoning quality matters more than Sol's lower price and faster positioning.
Explore GPT-6 Astra →Consumer
GPT-6 Luna
Choose GPT-6 Luna for focused, high-volume tasks where throughput and token cost matter more than Sol's coding and agentic depth.
Explore GPT-6 Luna →Consumer
Claude Opus 5.5
Compare Claude Opus 5.5 when evaluating another frontier model for coding, research, document work and autonomous workflows.
Explore Claude Opus 5.5 →Questions
GPT-6 Sol FAQs
What is GPT-6 Sol?
GPT-6 Sol is an OpenAI model built for complex coding and agentic workflows. It brings GPT-6 capabilities into a faster and more affordable tier below GPT-6 Astra.
How much does GPT-6 Sol cost?
Standard short-context API pricing is $2 per million input tokens, $0.20 per million cached input tokens, $2.50 per million cache-write tokens and $10 per million output tokens. Input above 272K tokens triggers higher long-context rates for the full request.
What is the GPT-6 Sol context window?
The documented context window is 1,050,000 tokens, with a maximum output of 128,000 tokens.
What reasoning settings does GPT-6 Sol support?
It supports none, low, medium, high, xhigh and max reasoning effort. Medium is the documented default.
Can GPT-6 Sol use tools?
Yes. Through the Responses API it supports web and file search, image generation, code interpreter, hosted shell, apply patch, skills, computer use, MCP and tool search, as well as function calling.
Should I use GPT-6 Sol or GPT-6 Astra?
Use Sol when you need complex coding or agentic reasoning at a substantially lower token rate. Use Astra when the task justifies OpenAI's most capable tier and quality matters more than price.
What is the GPT-6 Sol API model ID?
Use gpt-6-sol in OpenAI API requests. The Responses API is the recommended path when you need built-in tools and reasoning controls.
Bottom line
Our GPT-6 Sol verdict
GPT-6 Sol is the practical GPT-6 tier for teams building demanding coding and agent workflows at production scale. Its 1.05M-token context, broad tool support and $2/$10 standard pricing create a strong middle ground between the inexpensive Luna tier and the more capable but substantially more expensive Astra tier. Teams should still evaluate their own tasks and monitor the long-context pricing threshold rather than assuming the largest context is always economical.
Visit GPT-6 Sol website ↗Similar Consumer Tools
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