gpt-6-astra — API, Pricing & Context Window | Vivgrid
Run OpenAI's gpt-6-astra on Vivgrid: the flagship gpt-6 coding model with a 1.05M-token context window, geo-distributed acceleration, and a unified API.
gpt-6-astra opens OpenAI's gpt-6 generation and succeeds gpt-5.6-sol. It pairs a 1.05M-token context window with a step up in multi-step reasoning and tool use, built for whole-repository refactors, long-running agents, and workflows where output quality outweighs token cost.
On Vivgrid, gpt-6-astra 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-astra 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 and Pi, work against the same key.
Specifications
| Provider | OpenAI |
| Model ID | gpt-6-astra |
| Best for | Coding |
| Available on | Chat Completions, Vibe coding |
| Context window | 1,050,000 tokens |
| Max output | 128,000 tokens |
| Modalities | Text, Image |
| Tool / function calling | Yes |
| Knowledge cutoff | 2026-06 |
| Acceleration | ⚡ Geo-Distributed — AMER, EMEA, APAC |
Pricing
Pricing in USD per 1M tokens, matching the provider's rates.
| Input | Cached input | Output |
|---|---|---|
| $10.00 | $1.00 | $50.00 |
What one request costs
The rates above applied to a 20K-token prompt with a 2K-token reply — a typical single agent turn, small enough that every request is billed at the base rate.
| Request | Cost |
|---|---|
| Cold prompt, nothing cached | $0.3000 |
| Warm prompt, 90% of the input served from cache | $0.1380 |
Prompt caching is billed at $12.50 per 1M cache-write tokens, with cached reads at $1.00.
Requests beyond 272K input tokens are billed at the long-context rate: $20.00 input / $2.00 cached input / $25.00 cache write / $75.00 output per 1M tokens.
API surfaces
The Vivgrid Console catalogs gpt-6-astra on 2 surfaces, all behind the same API key. The endpoint shown is the one the Console previews for that surface.
| Surface | Primary endpoint | Use it for |
|---|---|---|
| Chat Completions | /chat/completions | Agent projects, where Vivgrid injects the model, system prompt and tools server-side, and Model API calls that name the model per request. |
| Vibe coding | /chat/completions | Coding CLIs and IDE agents that drive the model themselves — point the tool at Vivgrid and keep your own loop. |
Quick start
Get an API key from the Vivgrid Console, then call gpt-6-astra directly.
curl https://api.vivgrid.com/v1/chat/completions \
-H "Authorization: Bearer $VIVGRID_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-6-astra",
"messages": [
{ "role": "user", "content": "Say hello in English, Chinese and Spanish." }
],
"stream": true
}'Choosing within the gpt-6 family
Prices are USD per 1M tokens at the base rate. Rows marked this page are the model described here.
| Model | Context | Max output | Input | Output |
|---|---|---|---|---|
gpt-6-astra — this page | 1,050,000 | 128,000 | $10.00 | $50.00 |
gpt-6.1-sol | 1,050,000 | 128,000 | $2.00 | $10.00 |
gpt-6-sol | 1,050,000 | 128,000 | $2.00 | $10.00 |
gpt-6-luna | 1,050,000 | 128,000 | $0.10 | $0.50 |
Ideal use cases
- Frontier coding agents and CLI tools (Codex, OpenCode, Claude Code-style flows)
- Whole-codebase reads and edits in a single 1.05M-token pass
- High-stakes reasoning where answer quality outweighs token cost
- Long agent traces that chain many tool calls across a session
Related models
- gpt-6.1-sol — the balanced gpt-6 model at a fifth of the price
- gpt-6-luna — the fast, low-cost gpt-6 model
- claude-fable-5-1 — Anthropic's most capable model
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claude-haiku-4-5 on Vivgrid: Anthropic's fast, low-cost Haiku model with a 200K context window, Messages API, and geo-distributed acceleration.
gpt-6.1-sol
Run OpenAI's gpt-6.1-sol on Vivgrid: the latest balanced gpt-6 model with a 1.05M-token context window, 128K max output, geo-distributed acceleration, and a unified API.