OpenAIOpenAI·text

GPT-6 Astra

VisionReasoningWeb searchFunction calling
Advertised as gpt-6-astraopenai-gpt-6-astra
Quick reference
GPT-6 Astra — TLDR
  • 🆕 OpenAI's flagship GPT-6 model, released September 2026.
  • 📏 1.05M-token context: 922K input, 128K output.
  • 🧠 Built for complex reasoning, coding, computer use, research, documents.
  • 👁️ Accepts text and image inputs; supports function calling and web search.
  • 🎯 On OpenAI's reported Terminal-Bench 4.0, 57.9% versus 37.3% for GPT-5.6 Sol.
  • 💬 Asks clarifying questions more often; stays coherent on long tasks.
  • 🔧 New Codex context preservation replaces summary-style compaction in long sessions.
  • 🏢 Staged rollout: Trusted Access Program first, then API and paid plans.
💰 Best price on AntSeed
$0.350 / $2.00
per 1M · cheapest in / out
📏 Context
1.1M tokens
🐜 Sellers
10
advertising on AntSeed
Provider

OpenAI is an American artificial intelligence research organization headquartered in San Francisco, structured as both a for-profit public benefit corporation and a nonprofit foundation. The lab developed the GPT family of large language models, the DALL-E image generation…

Explore 27 more models by OpenAI
About this model

GPT-6 Astra opens OpenAI's GPT-6 generation and is positioned by OpenAI as its most capable model, aimed at "the hardest end-to-end work": complex reasoning, software engineering, computer use, research, and document creation. In the API it is presented as the default starting point for complex reasoning and coding tasks. It accepts text and image inputs, supports tool/function calling and web search, and exposes a 1,050,000-token context window with up to 128,000 output tokens.

Compared with the July 2026 GPT-5.6 line — GPT-5.6 Sol, GPT-5.6 Luna, and GPT-5.6 Terra, plus their Pro variants such as GPT-5.6 Sol Pro — OpenAI's own model guidance says Astra is more intelligent and capable than GPT-5.6 Sol and earlier models, stays more coherent during long tasks, follows longer instructions better, and is more likely to ask clarifying questions instead of assuming. On OpenAI's reported figures, Astra reaches 57.9% on Terminal-Bench 4.0 against 37.3% for GPT-5.6 Sol, and 100% versus 78.5% on the company's ExploitBench evaluation.

Architecturally, the notable operational change is how long sessions are handled: with Astra, Codex uses a new mechanism to preserve and retrieve context once the window fills, rather than the summarizing compaction earlier models relied on. OpenAI also describes stronger visual judgment for generated interfaces and the ability to build and host sites and apps from a prompt.

OpenAI rolled the model out first through its Trusted Access Program before broader API and paid-plan availability. Earlier generations such as GPT-5.5 Pro and GPT-5.3 Codex remain available for lighter or cheaper workloads.

Sources
developers.openai.comGPT-6 Astra Model | OpenAI API· developers.openai.comopenai.comGPT-6 Astra: A new generation of intelligence | OpenAI· openai.com

This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.

Usage on AntSeed
Tokens served
879.02M
input + output
Requests
7,051
settled calls
Buyers
20
distinct, on this model
Sellers used
8
of 10 advertising
Settled
$156.15
gross USDC, this model
Sellers serving GPT-6 Astra (10)compare on the network explorer →
SellerReputationRoutingInput $/MCached $/MOutput $/MCategoriesAPI

"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = on-chain trust (0-100). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.