Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
| Attribute | GPT-6 Solgpt-6-sol | Aura-2aura-2 | GPT-6 Sol Progpt-6-sol-pro |
|---|---|---|---|
| Pricing | |||
| Input | $2.00 / 1M | $0 / 1M | $2.00 / 1M |
| Output | $10.00 / 1M | $0 / 1M | $10.00 / 1M |
| Cache Write (5m) | $2.00 / 1M | Not applicable | $2.00 / 1M |
| Cache Write (1h) | $2.00 / 1M | Not applicable | $2.00 / 1M |
| Cache Read | $2.00 / 1M | Not applicable | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1.1M | N/A | 1.1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | No | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | OpenAI | Deepgram | OpenAI |
| Category | chat | voice | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | 2026-07-16 | — |
| Description | |||
| Summary | GPT-6 Sol is OpenAI's cost-efficient high-end model in the GPT-6 series, positioned between the flagship GPT-6 Astra and the fast GPT-6 Luna tier. It is designed for professional knowledge work, agentic coding, business workflow automation, and computer-use tasks, with particular strength in long-horizon software engineering across real-world codebases. GPT-6 Sol approaches Astra-level factual reliability at a significantly lower cost, while sharing its clear and concise communication style. This balance of capability, reliability, and efficiency makes it well suited for production agents, complex engineering workflows, and scalable professional applications | Deepgram Aura-2 text-to-speech for real-time voice applications. Billed per input character. | GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex and demanding tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is particularly well suited for agentic coding, long-horizon software engineering, professional analysis, and complex automated workflows where solution quality takes priority over latency and cost. |