Claude Sonnet 5.5 and GPT-6 Sol are similarly priced general-purpose models for demanding coding and agent workflows. Both start at $2 per million input tokens, $0.20 per million cached input tokens and $10 per million output tokens. That apparent tie ends when context grows, tools differ or an application needs a particular provider ecosystem.
This comparison uses Anthropic and OpenAI documentation for specifications and keeps vendor benchmarks attributed to their source. We have not independently benchmarked the two models.
Quick verdict
Choose Claude Sonnet 5.5 when Anthropic’s tool behavior, cloud availability or agent workflow fits your stack and you expect large prompts without OpenAI’s long-context price step. Choose GPT-6 Sol when the Responses API tool suite, OpenAI ecosystem or Sol’s reasoning controls fit the application better.
At standard prompt sizes, price alone does not decide the winner. Run both on the same evaluation set and compare successful-task cost.
Sonnet 5.5 vs GPT-6 Sol specs
| Feature | Claude Sonnet 5.5 | GPT-6 Sol |
|---|---|---|
| Model ID | claude-sonnet-5-5 | gpt-6-sol |
| Standard input | $2/M | $2/M |
| Cached input | $0.20/M | $0.20/M |
| Standard cache write | $2.50/M | $2.50/M |
| Standard output | $10/M | $10/M |
| Context window | 1,000,000 | 1,050,000 |
| Maximum output | 128,000 | 128,000 |
| Input and output | Text/image to text | Text/image to text |
| Reasoning | Adaptive, high default | None through max, medium default |
| Primary agent API | Claude Messages API | Responses API |
Both support batch-style lower-cost processing, although the product semantics and operational guarantees differ. Compare the exact processing mode rather than assuming the same label means the same service.
Pricing: equal until Sol crosses 272K input
For standard requests at or below 272,000 input tokens, base rates align:
| Billing item | Sonnet 5.5 | GPT-6 Sol |
|---|---|---|
| Input | $2.00 | $2.00 |
| Cached input | $0.20 | $0.20 |
| Cache write | $2.50 | $2.50 |
| Output | $10.00 | $10.00 |
Prices are per million tokens. Sonnet also documents a $4 one-hour cache write. OpenAI applies a higher rate to the complete GPT-6 Sol request when input exceeds 272K tokens: $4 input, $0.40 cached input, $5 cache writes and $15 output per million tokens.
That makes prompt size an important decision factor. A nominally similar 500K-context workload can have different list-price economics. Do not split a request merely to avoid a price tier unless the resulting architecture preserves quality and reliability.
Batch and Flex processing for Sol list lower prices but serve different operating needs. Anthropic’s batch path is also asynchronous. Neither should be compared directly with an interactive standard request without latency and availability requirements.
Context and output limits
Sol documents a 1,050,000-token context window, slightly above Sonnet’s 1,000,000. Both allow up to 128,000 output tokens. The 50K context difference is less important than retrieval quality, cache reuse and pricing beyond the long-context threshold.
Long-context evaluations should test where crucial instructions appear, how retrieved evidence is ranked and whether the model cites the right source. The long-context models guide explains why maximum window size is not the same as effective recall.
Reasoning controls
Sonnet 5.5 uses adaptive thinking and defaults to high effort. It supports between_tools behavior at high effort or below, with constraints around preserved thinking and model switching.
GPT-6 Sol offers none, low, medium, high, xhigh and max, with medium as the default. OpenAI’s Chat Completions function calling works only when reasoning is none, while the Responses API is the intended surface for richer agentic tool use.
These are different programming models. Do not translate one provider’s effort label into the other’s. Test latency, token use and acceptance at the exact settings you will deploy.
Tools and agent architecture
OpenAI documents Responses API support for functions, web search, file search, computer use, image generation, code interpreter, hosted shell, apply patch, skills, MCP and tool search for GPT-6 Sol. Tool availability can depend on endpoint and account configuration.
Anthropic documents tool use, computer use, vision, PDFs, Files API workflows, prompt caching and batch processing for Sonnet 5.5. It also changed forced-tool and computer-use semantics from Sonnet 5, so existing agents need migration tests.
The better tool stack is the one that maps to your infrastructure and security model. Consider network isolation, credentials, approval boundaries, observability and retry behavior through the AI Security hub and AI Operations hub.
Coding performance and benchmark evidence
Anthropic’s Sonnet 5.5 launch material reports strong results on Terminal-Bench 4 and FrontierCode, and includes cross-model figures for GPT-6 Sol. OpenAI documents Sol as its workhorse for coding and everyday demanding work.
Cross-vendor benchmark claims must remain attributed. Different providers may use different harnesses, effort levels and tools. A score copied from Anthropic’s table is not an independent OpenAI claim, and a product description is not a measured result.
Evaluate repository-level tasks that represent your work: bug fixes, test generation, code review, tool failures and rollback. The AI model evaluation checklist provides dimensions for quality, latency, cost, reliability and safety.
OpenAI also corrected a GPT-6 image-encoding issue on September 25, 2026. Teams that evaluated Sol’s vision behavior before that correction should rerun relevant tests rather than carrying old vision results forward.
Provider and governance fit
Sonnet 5.5 is offered through Anthropic and supported cloud channels including AWS, Google Cloud and Microsoft Foundry. GPT-6 Sol is available through OpenAI’s API surfaces, with product-specific availability elsewhere.
Data residency, zero-retention eligibility, model policies and regional availability can be more important than a benchmark difference. Confirm current terms for the exact provider and endpoint. GitHub Copilot availability for either model is a separate entitlement and billing surface, not proof of direct API access.
Decision framework
Start with Sonnet 5.5 when:
- your stack already uses Anthropic’s Messages API
- prompts commonly exceed 272K input tokens
- Anthropic’s tool and cloud-provider fit is stronger
- you need a fast, current Sonnet model at $2/$10
Start with GPT-6 Sol when:
- your application is built around the Responses API
- OpenAI’s hosted tools reduce integration work
- explicit reasoning levels match your routing strategy
- OpenAI deployment and governance requirements fit better
Evaluate both when model quality directly affects revenue, safety or reviewer workload. The models have close enough base pricing that empirical results can outweigh a paper comparison.
Migration and testing checklist
- create an identical golden dataset for both models
- hold tools and permissions constant where possible
- record provider, model ID, effort and endpoint
- measure cache hits and prompt sizes
- test streaming and interrupted tool calls
- validate structured outputs and retry paths
- separate vision results from text-only results
- compare accepted-task cost, not only token price
- canary the selected model before full rollout
Use the LLM regression-testing guide and canary-deployment guide for the release process.
My take
This is a genuine evaluation decision rather than a pricing-table winner. Sonnet 5.5 and GPT-6 Sol begin at the same rates and have nearly identical context and output limits. Sonnet’s advantage can emerge in large-context pricing and Anthropic-oriented stacks. Sol’s advantage can emerge from the Responses API and hosted tool ecosystem. The best choice should come from your own acceptance tests.
Specifications were checked against Anthropic’s Sonnet 5.5 model overview, OpenAI’s GPT-6 Sol model documentation and OpenAI API pricing.
Frequently asked questions
Which model is cheaper?
At standard rates up to 272K GPT-6 Sol input, both list $2 input and $10 output per million tokens. Sol becomes more expensive for the whole request above its 272K input threshold.
Which has more context?
GPT-6 Sol lists 1.05M tokens and Sonnet 5.5 lists 1M. Both support up to 128K output.
Which is better for coding agents?
There is no universal answer. Compare both using your repository, tools, effort settings and acceptance criteria.
Can I use both behind one router?
Yes, but normalize provider errors and tool contracts carefully. Avoid switching models inside preserved-thinking conversations without a tested compatibility design.
Are GitHub Copilot versions the same as direct API access?
No. Copilot availability, policies and billing are separate from Anthropic or OpenAI API accounts.