GPT-6.1 Sol
OpenAI GPT-6 Sol upgrade with near-Astra performance for coding, computer use and professional work at a lower cost
GPT-6.1 Sol is an OpenAI general-purpose model for coding agents, complex document understanding, computer use and multi-step business workflows.
starsCapabilities
paymentsContext and pricing
descriptionOverview
Overview
GPT-6.1 Sol is a general-purpose model in the official OpenAI model catalog, with model ID gpt-6.1-sol. It should be evaluated for text understanding, generation, coding assistance, structured processing and multimodal product capabilities rather than single-purpose image generation, transcription or TTS.
Best for
Use GPT-6.1 Sol as a core candidate for assistants, complex Q&A, coding, long-form analysis, workflow automation and vision-enabled applications. Before production, compare context length, pricing, latency, tool support and real output quality.
Official specifications and pricing
GPT-6.1 Sol launched on September 29, 2026 with API model ID gpt-6.1-sol as an upgrade to GPT-6 Sol. Near-Astra performance refers to OpenAI's specific evaluations; compare quality and cost on your own tasks.
Supports text and image input with text output, a 1,050,000-token context window and up to 128,000 output tokens. The knowledge cutoff is 2026-04-30.
reasoning.effort supports low, medium (default), high, xhigh and max, but not none or minimal. Streaming, function calling and structured outputs are supported. Tool calling requires the Responses API; Chat Completions is supported without tool calling.
As verified on 2026-09-30, standard text pricing per million tokens is $2 input, $0.10 cached input, $2.50 cache writes and $10 output. Prompts exceeding 272K input tokens incur 2x input and cache rates and 1.5x output rates for the full request. Fast costs 2x Standard; Batch and Flex cost 50% of Standard. Regional processing adds a 10% premium where available, and tool calls may incur additional fees.
Audio, video and fine-tuning are not supported. Image generation is a Responses API tool capability, not direct image output from the model.
lightbulbUse cases
- Assistants and complex Q&A
- Code generation and code review
- Content generation, summarization and rewriting
- Structured extraction and automation
thumb_upStrengths
- Useful for general production workloads
- Covers text understanding and generation
- Easy to compare with smaller variants
- Good core model for agent and tool workflows
infoLimitations
- Capabilities and pricing depend on official OpenAI documentation
- Higher-quality models usually cost more and add latency
- Complex workflows still need prompts, tools and evaluation
- Not a replacement for dedicated image, transcription or TTS models
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