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OpenAI's mid-tier reasoning model with configurable effort levels, a 1.05M-token context window, and text+image input for coding and agentic workflows.
Limitations. OpenAI has not disclosed parameter count or architecture details for gpt-6-sol; its documented training data cutoff is April 20, 2026, so claims about raw capability beyond that rest on vendor positioning rather than published specs. Output is capped at 128,000 tokens per response, and the model accepts only text and image input — there is no audio input or output. Domain performance outside code and math (legal, medical, finance, and similar) is currently an estimate rather than a benchmarked figure, so treat it as a starting point, not a guarantee.
Sovereignty note. gpt-6-sol is built by OpenAI, a US-headquartered creator, and is served as a hosted commercial API rather than a self-hosted deployment. OpenAI documentation confirms EU data residency is available for this model under Standard processing, but does not confirm CLOUD Act exposure or a training-on-input policy for this endpoint, so it should not be treated as a Sovereign option without further verification.
| Inference Provider | Sovereignty | Runs in | In / out per 1M | Status | Pin |
|---|---|---|---|---|---|
| L0 | €1.80 / 8.98+7 rates | Online |
18 use cases classified by the curator. The note says why.
Tool-calling + extended-thinking for iterative code generation and repair; 1.05M context supports full codebase + test history.
Vision capability for screenshot understanding + tool-calling for DOM interaction + extended-thinking for multi-step navigation logic.
Vision capability for chart parsing; tool-calling enables structured data output; extended-thinking interprets complex multi-axis relationships.
1.05M context window holds full repository context; extended-thinking enables deep architectural reasoning; tool-calling can integrate CI/CD feedback.
1.05M context window fits entire long documents; vision handles scanned PDFs; extended-thinking supports complex reasoning over document content.
Native tool-calling support with 1.05M context window for managing large function inventories and call histories.
Tool-calling can enforce classification taxonomy, but model's extended-thinking and 1.05M context are over-provisioned for typical classification workloads.
Tool-calling can formalize entity schemas, but vision + extended-thinking not essential for standard entity extraction.
Sourced numbers, not our own evaluations. Percentiles are against the whole Stav catalogue.
Computed from aa-intelligence-index, gpqa-diamond, aa-engineering-index, aa-coding-index, livecodebench, terminal-bench-v4, aa-lcr.
curl https://api.stav.ai/v1/chat/completions \
-H "Authorization: Bearer $STAV_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-6-sol",
"reasoning_effort": "high",
"messages": [{"role": "user", "content": "Hello!"}]
}'→ X-Stav-Request-Id · X-Stav-Model · X-Stav-Provider → X-Stav-Sovereignty-Level — the rung the request was served at