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OpenAI · New 2026 Frontier Model

GPT Astra 6 API Pricing & Token Cost Calculator (2026)

GPT Astra 6 (also called ChatGPT Astra or GPT-6 Astra) costs$10.00 per million input tokens and $50.00 per million output tokens. Use our free GPT Astra 6 token cost calculator to estimate your API spend — and compare with Claude Fable 5.1, GPT-4o, and 50+ other models.

Input$10.00 / 1M
Output$50.00 / 1M
Cached$1.00 / 1M
Context1,050,000 tok
Batch50% off

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GPT Astra 6 API Pricing Breakdown

All prices per million tokens as of September 2026.

TierInput /1MOutput /1MType
GPT Astra 6 (Standard)$10.00$50.00Flagship
GPT Astra 6 (Batch API)$5.00$25.0050% off
GPT Astra 6 (Cached)$1.00$50.00Cached in

* Verify latest prices at platform.openai.com/pricing

What Makes GPT Astra 6 Different?

⚡

Sub-20ms Audio Latency

Native omni-modal streaming processes audio, video, and text simultaneously with near-human response speed — enabling real-time conversational AI at scale.

🧠

1,050,000 Token Context

The largest context window of any OpenAI model. Process an entire codebase, book, or legal document in a single API call.

🤖

Astra-Agentic Subsystem

Specialized instruction-following for complex autonomous tasks. Requires fewer explicit rules to execute multi-step API orchestration and coding workflows.

⚙️

Dynamic Token Sizing

Automatically adjusts internal precision based on task complexity, lowering output latency and compute cost for simpler requests.

99.1%
HumanEval Win Rate
3x
Compute Efficiency
20ms
Audio Latency
1.05M
Context Tokens

GPT Astra 6 Real-World Cost Examples

Full-repo code review (1M tokens)

In: 1,000,000 tokensOut: 10,000 tokens
per call$10.50

~$105.00 at 10 reviews/mo

Enterprise document analysis

In: 200,000 tokensOut: 5,000 tokens
per call$2.25

~$225.00 at 100 docs/mo

Multi-turn agentic workflow

In: 50,000 tokensOut: 20,000 tokens
per call$1.50

~$150.00 at 100 runs/mo

Real-time audio + text streaming

In: 10,000 tokensOut: 3,000 tokens
per call$0.25

~$750.00 at 3,000 sessions/mo

GPT Astra 6 vs Other 2026 LLMs — Cost Comparison

How does GPT Astra 6 pricing compare across the 2026 frontier model landscape?

ModelProviderInput /1MOutput /1MContext
GPT-6 Astrathis pageOpenAI$10.00$50.001,050,000
Claude Fable 5.1Anthropic$10.00$50.001,000,000
GPT-4oOpenAI$2.50$10.00128,000
Claude Sonnet 5Anthropic$2.00$10.001,000,000
Gemini 3.8 FlashGoogle$0.75$3.751,000,000
→ Compare all 50+ models in the full LLM token cost calculator

5 Ways to Reduce Your GPT Astra 6 API Costs

  1. 1

    Use Batch API for 50% off

    Any non-real-time task — document analysis, code review, bulk classification — can use OpenAI's Batch API at $5.00/M input. This alone cuts your bill by 50% for background workloads.

  2. 2

    Enable prompt caching (90% off repeated context)

    At $1.00/M for cached tokens vs $10.00/M standard, caching is critical at GPT Astra 6's price tier. Any app with a large, fixed system prompt or document context should architect for cache hits first.

  3. 3

    Downgrade to GPT-4o for standard tasks

    GPT Astra 6 is 4× more expensive than GPT-4o ($10.00 vs $2.50/M input). Route only tasks that genuinely require 1M context windows or multimodal streaming to Astra 6. Use GPT-4o for everything else.

  4. 4

    Optimize output length with max_tokens

    At $50.00/M, output tokens are extremely expensive. Set strict max_tokens limits and instruct the model to be concise. Saving 100 output tokens per call saves $0.005 — trivial per call, but significant at scale.

  5. 5

    Build a tiered routing system

    GPT Astra 6 → GPT-4o → GPT-4o mini routing by task complexity. Route only the top 5–10% of queries to Astra 6. The remaining 90% on GPT-4o mini costs 66.7× less per input token.

GPT Astra 6 Pricing — Frequently Asked Questions

How much does GPT Astra 6 cost per token?
GPT Astra 6 costs $10.00 per million input tokens and $50.00 per million output tokens at standard pricing. With the Batch API, costs drop 50% to $5.00/M input and $25.00/M output. Prompt-cached input tokens are $1.00/M — a 90% discount on repeated context. Use our free calculator to estimate your exact costs.
Is GPT Astra 6 more expensive than Claude Fable 5.1?
No. GPT Astra 6 and Claude Fable 5.1 are priced identically at $10.00/M input and $50.00/M output tokens — both are frontier-tier flagship models at the same price point. The key differences are in capability: GPT Astra 6 leads in real-time multimodal streaming (sub-20ms audio latency), while Claude Fable 5.1 leads in sustained reasoning and massive codebase ingestion with a 97.5% prompt caching discount vs GPT Astra 6's 90%.
What is the GPT Astra 6 context window?
GPT Astra 6 has a 1,050,000-token context window — the largest of any OpenAI model. This allows processing approximately 3,150 pages of text, or a large codebase, in a single request. At $10.00/M input, processing the full context costs $10.50 per request, making prompt caching critical for repeated large-context workflows.
What is the difference between GPT Astra 6 and GPT-4o?
GPT Astra 6 is OpenAI's 2026 frontier flagship — it's significantly more capable and expensive than GPT-4o. GPT-4o costs $2.50/M input vs GPT Astra 6's $10.00/M — a 4× price difference. GPT Astra 6 adds a 1,050,000-token context window (vs 128,000), native omni-modal streaming, and the Astra-Agentic subsystem for complex autonomous tasks. Use GPT-4o for standard production workloads; use GPT Astra 6 for frontier-tier complex reasoning and multimodal tasks.
How do I access GPT Astra 6 via API?
Access GPT Astra 6 through the OpenAI API using the model ID 'gpt-astra-6' (verify the exact string at platform.openai.com). You'll need an OpenAI API key and your account must be on a Tier 4+ usage plan for full rate limits. The Batch API variant gives 50% off for async workloads.
Does GPT Astra 6 support prompt caching?
Yes. GPT Astra 6 supports prompt caching at $1.00/M for cached input tokens — a 90% discount vs the $10.00/M standard rate. Cache writes are charged at standard input pricing. For applications with large, repeated system prompts or documents (e.g., RAG, codebase agents), enabling prompt caching is essential to keep costs manageable.

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