# gpt-6-sol — API, Pricing & Context Window | Vivgrid

> Source: https://vivgrid.com/docs/models/gpt-6-sol

Run OpenAI's gpt-6-sol on Vivgrid: the balanced gpt-6 model with a 1.05M-token context window, 128K max output, geo-distributed acceleration, and a unified API.

`gpt-6-sol` is the balanced model in OpenAI's gpt-6 family, sitting below the flagship `gpt-6-astra`. It keeps the generation's **1.05M-token context window** and **128K-token max output** at a fifth of astra's per-token price, making it a practical default for production coding agents.

On Vivgrid, `gpt-6-sol` is served through a single OpenAI-compatible endpoint with **geo-distributed acceleration across AMER, EMEA, and APAC**, so requests are routed to the nearest compute region for lower latency. You can switch your agent to `gpt-6-sol` from the Console without changing a line of application code.

It is available on both OpenAI surfaces — **Chat Completions** (`/chat/completions`) and the **Responses API** (`/responses`) — so coding CLIs that expect the Responses wire format, such as [Codex](/docs/tutorials/codex) and [Pi](/docs/tutorials/pi), work against the same key.

<ModelSpec slug="gpt-6-sol" />

Prompt caching is billed at **$2.50 per 1M cache-write tokens**, with cached reads at $0.20.

Requests beyond **272K input tokens** are billed at the long-context rate: $4.00 input / $0.40 cached input / $5.00 cache write / $15.00 output per 1M tokens.

## Ideal use cases

- Production coding agents balancing quality, speed, and cost
- Coding CLIs on the Responses API (Codex, Pi, OpenCode)
- Whole-repository analysis within a 1.05M-token context
- High-volume tool-calling workflows that outgrow a small model

## Related models

- [gpt-6-astra](/docs/models/gpt-6-astra) — the gpt-6 generation flagship
- [gpt-6-luna](/docs/models/gpt-6-luna) — the fast, low-cost gpt-6 model
- [gpt-5.6-terra](/docs/models/gpt-5.6-terra) — the balanced gpt-5.6 model