gpt-5.6-sol
Input price$4
Output price$20
OpenAITextVision
gpt-6-astra
gpt-6-astra is OpenAI's model at $10.00 input and $50.00 output per million tokens, with a 1050K context window. On a typical 3:1 input-to-output mix that blends to roughly $20.00 per million tokens, placing it in the premium band of the 79 models tracked here — cheaper than 0% of them.
Context window1050K
Input price$10 / 1M
Output price$50 / 1M
Output speed58 tok/s
Quality score99
Data updatedUpdated Sep 2026
Price verified2026-09-16 · Official
Price noteGated to OpenAI's Trusted Access and Daybreak programs — standard accounts cannot use it. Above 272K input tokens the whole request bills at 2x input / 1.5x output ($20 / $75). Cache-hit input is $1.00 / 1M tokens; Batch is 50% off ($5 / $25); Fast mode is 2x ($20 / $100)
By price, gpt-6-astra ranks 75th cheapest of 79 on input and 76th on output. Its quality score of 99 ranks 1st of 79, and on value (quality score ÷ output price) it ranks 76th of 79. Its blended rate sits 533% above the catalog average.
In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $2,250 per month on gpt-6-astra, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $2,400. Because output is priced 5.0× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.
A 1050K context window holds roughly 1,400 pages of A4 text (at ~750 tokens per page), ranking 3rd of 79 here. That is enough to drop in an entire technical manual or several source files at once, which suits long-document summarization and codebase-wide analysis. Output runs at about 58 tok/s (72nd fastest of 79), which is better suited to asynchronous or background jobs.
We track 12 OpenAI models, and gpt-6-astra's blended rate sits 287% above that provider's average. If your task tolerates a little less headroom, gpt-5.6-sol (OpenAI) blends about 60% cheaper at a quality score of 98, and is worth benchmarking first. Nothing in the catalog scores higher on quality, so this is the ceiling.
The closest model in OpenAI's line-up is gpt-5.5 ($5.00 input / $30.00 output, quality 97). Against it, gpt-6-astra scores 2 points higher on quality, runs 27 tok/s slower (about 32%), has a 1K larger context window, costs 44% more blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.
Estimated monthly cost
Monthly API spend across four common workloads, next to the cheapest model we track.
| Workload | Usage assumption | This model | Cheapest model |
|---|---|---|---|
| Support chatbot | 2,000 input / 500 output tokens per turn, 50,000 turns per month | $2,250 | $3.00 |
| RAG document Q&A | 8,000 input / 800 output tokens per query, 20,000 queries per month | $2,400 | $3.84 |
| Coding assistant | 12,000 input / 2,000 output tokens per request, 10,000 requests per month | $2,200 | $3.20 |
| Batch summarization | 4,000 input / 400 output tokens per item, 200,000 items per month | $12,000 | $19 |
Derived directly from the rates on this page. Excludes prompt caching, batch discounts and free tiers.
How it compares
The alternatives worth benchmarking alongside it, from the same dataset.
| Model | Provider | Blended /1M | Quality | Price delta |
|---|---|---|---|---|
| gpt-6-astra | OpenAI | $20.00 | 99 | — |
| gpt-5.6-solCheaper option | OpenAI | $8.00 | 98 | -60% |
| gpt-5.5Same provider | OpenAI | $11.25 | 97 | -44% |
| qwen3.5Best value overall | Alibaba | $0.11 | 91 | -99% |
Best for
ReasoningCodingLong ContextMultimodal
Modalities
TextVision
Where it fits — and where it doesn't
Good fit
- Coding: writing, refactoring and debugging across multi-file project context.
- Reasoning: multi-step decomposition, planning and tasks that need rigorous inference.
- Long documents: a 1050K window ingests a full contract, paper or large codebase in one pass.
- Multimodal input: handles images, screenshots and scanned documents directly.
Poor fit
- High-frequency batch jobs: at $20.00 blended per million tokens, bills scale quickly at volume.
- Latency-critical interactive use: 58 tok/s makes long responses feel sluggish.
Frequently asked questions
How much does the gpt-6-astra API cost?
gpt-6-astra costs $10.00 per million input tokens and $50.00 per million output tokens. On a 3:1 input-to-output mix that blends to about $20.00 per million tokens.
What does gpt-6-astra cost per month?
It depends on volume. Using the four worked scenarios on this page: a support chatbot runs about $2,250/month, RAG document Q&A about $2,400/month, a coding assistant about $2,200/month, and batch summarization about $12,000/month. Plug your own token counts into the cost calculator for a tailored figure.
How large is the gpt-6-astra context window?
1050K tokens — roughly 1,400 pages of A4 text at ~750 tokens per page, ranking 3rd of the 79 models tracked here.
gpt-6-astra or gpt-5.6-sol — which is better value?
gpt-5.6-sol blends to about $8.00 per million tokens versus $20.00 for gpt-6-astra — roughly 60% cheaper — at a quality score of 98 against 99. If that quality gap does not show up on your task, take the cheaper one; if it does, stay with gpt-6-astra. Benchmark both on your own data before deciding.
What is gpt-6-astra best suited for?
Tagged use cases: reasoning, coding, long-context, multimodal. Coding: writing, refactoring and debugging across multi-file project context. Less suitable: High-frequency batch jobs: at $20.00 blended per million tokens, bills scale quickly at volume.
How current is this gpt-6-astra pricing?
Pricing here was last verified on 2026-09-16 against official documentation. llmprice.app runs a daily collection job, but providers can change rates between runs — confirm against OpenAI's official pricing page before you commit.
Estimate the real cost of this model
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Pricing, speed and quality scores change over time. Confirm official documentation before production use.