openai
OpenAI: GPT-6 Sol
openai/gpt-6-sol
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenAI's gpt-6-sol is described by the OpenRouter catalog as the cost-efficient high-end entry in the GPT-6 series, positioned between the flagship Astra and fast Luna tiers. The catalog lists text, image, and file inputs with text-only output, a context window of roughly one million tokens, optional reasoning enabled by default at medium effort and adjustable from none to max, plus support for tools, structured outputs, and prompt caching. No independent model card was included in this source pack, so all capability claims rest on the catalog listing alone.[1]
Strengths
- Accepts text, image, and file inputs and exposes a context window of about one million tokens, according to the catalog.[1]
- Reasoning is optional and tunable across several effort levels, enabled by default at medium rather than mandatory.[1]
- Catalog lists support for tool calling, structured outputs, seed, verbosity, and prompt caching.[1]
Limitations
- Evidence comes only from the OpenRouter catalog; no independent model card was available in this pack, so behavior should be validated on real workloads before adoption.[1]
- Output is text-only, the knowledge cutoff is not reported, and the coding and agentic benchmark indices were left unpopulated, so measured performance data is thin.[1]
Where to use it
- Long-document or file-heavy analysis where a very large context window may help; verify throughput and cost on your own data first.[1]
- Image-plus-text understanding tasks such as screenshot or document question answering, as a suggestion pending workload testing.[1]
- Assistant workflows that rely on tool calls and structured outputs, noting that agentic performance was not measured in the supplied evidence.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-6 SolSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-6 Sol is the cost-efficient high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra and above the fast GPT-6 Luna tier. It is suited for demanding professional...
Specifications
- Model ID
- openai/gpt-6-sol
- Canonical ID
- openai/gpt-6-sol-20260922
- Creator
- openai
- Added to OpenRouter
- 22.09.2026
- Context length
- 1,050,000
- Modality
- text+image+file->text
- Input modalities
- file, image, text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $2 / out $10
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | AA — next 20% of the cohort | reasoning: optional · default medium · efforts: max, xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · default medium · efforts: max, xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Intelligence index | 44.2 | AA — next 20% of the cohort | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| OpenAI | 1,050,000 | $1 | $5 | — | — | 100% |
| Amazon Bedrock | 1,050,000 | $2 | $10 | — | — | 100% |
| OpenAI | 1,050,000 | $2 | $10 | — | — | 100% |
| Azure | 1,050,000 | $2 | $10 | — | — | 100% |
| Azure | 1,050,000 | $2.2 | $11 | — | — | 100% |
| Azure | 1,050,000 | $2.2 | $11 | — | — | 100% |
| Amazon Bedrock | 1,050,000 | $2.2 | $11 | — | — | — |
| OpenAI | 1,050,000 | $4 | $20 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.