Choose Anthropic: Claude Opus 4.7 if…
No advantage on the data we track — pick it for provider preference or output quality on your own prompts.
Anthropic: Claude Opus 4.7 vs OpenAI: GPT-6 Astra Pro (batch)
OpenAI: GPT-6 Astra Pro (batch) comes out ahead on the data we track: 2 advantages and none for Anthropic: Claude Opus 4.7.
Key numbers
| Spec | Anthropic: Claude Opus 4.7 | OpenAI: GPT-6 Astra Pro (batch) |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Input price (per 1M tokens) | $5.00 | $5.00 |
| Output price (per 1M tokens) | $25.00 | $25.00 |
| Blended price (3:1 input/output) | $10.00 | $10.00 |
| Cheaper than … of all models we track | 5% | 5% |
| Context window | 1M tokens (~1,500 pages) | 1.1M tokens (~1,575 pages) |
| Larger context than … of all models | 69% | 93% |
| Max output per response | 128K tokens (~96,000 words) | 128K tokens (~96,000 words) |
| Input types | text, image, file | file, image, text |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2026-04-16 | 2026-09-04 |
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What it costs for real workloads
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | Anthropic: Claude Opus 4.7 | OpenAI: GPT-6 Astra Pro (batch) | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $875 | $875 | — |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $850 | $850 | — |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $900 | $900 | — |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $550 | $550 | — |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $275 | $275 | — |
Capabilities side by side
| Capability | Anthropic: Claude Opus 4.7 | OpenAI: GPT-6 Astra Pro (batch) | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | ✓ Yes | ✓ Yes | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | ✓ Yes | ✓ Yes | answer from live web results |
| Seed (reproducible sampling) | — | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | — | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
- Anthropic: Claude Opus 4.7: price unchanged since we started tracking it on 2026-08-06.
- OpenAI: GPT-6 Astra Pro (batch): price unchanged since we started tracking it on 2026-09-05.
Which should you choose?
Choose OpenAI: GPT-6 Astra Pro (batch) if…
- you need seed (reproducible sampling) — to repeat a generation for tests and evals; Anthropic: Claude Opus 4.7 does not advertise it
- you want the newer model — released 2026-09-04, 5 months after the other
Frequently asked questions
Is Anthropic: Claude Opus 4.7 better than OpenAI: GPT-6 Astra Pro (batch)?
OpenAI: GPT-6 Astra Pro (batch) comes out ahead on the data we track: 2 advantages and none for Anthropic: Claude Opus 4.7.
Which is cheaper, Anthropic: Claude Opus 4.7 or OpenAI: GPT-6 Astra Pro (batch)?
They cost the same: $10.00 per 1M tokens at a 3:1 input/output mix.
How much do Anthropic: Claude Opus 4.7 and OpenAI: GPT-6 Astra Pro (batch) cost per million tokens?
Anthropic: Claude Opus 4.7 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens; OpenAI: GPT-6 Astra Pro (batch) costs $5.00 input and $25.00 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Anthropic: Claude Opus 4.7 or OpenAI: GPT-6 Astra Pro (batch)?
OpenAI: GPT-6 Astra Pro (batch): 1.1M tokens, about 1,575 pages, against 1M (about 1,500 pages) for Anthropic: Claude Opus 4.7.
Do Anthropic: Claude Opus 4.7 and OpenAI: GPT-6 Astra Pro (batch) support function calling and JSON output?
Tool calling — Anthropic: Claude Opus 4.7: yes, OpenAI: GPT-6 Astra Pro (batch): yes. JSON-schema structured output — Anthropic: Claude Opus 4.7: yes, OpenAI: GPT-6 Astra Pro (batch): yes.
Can Anthropic: Claude Opus 4.7 or OpenAI: GPT-6 Astra Pro (batch) read images?
Yes, both accept image input.
Is Anthropic: Claude Opus 4.7 or OpenAI: GPT-6 Astra Pro (batch) free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Anthropic: Claude Opus 4.7 and OpenAI: GPT-6 Astra Pro (batch)?
Anthropic: Claude Opus 4.7 can write up to 128K tokens (about 96,000 words) per response; OpenAI: GPT-6 Astra Pro (batch) up to 128K (about 96,000 words).
When were Anthropic: Claude Opus 4.7 and OpenAI: GPT-6 Astra Pro (batch) released?
Anthropic: Claude Opus 4.7 was listed on 2026-04-16; OpenAI: GPT-6 Astra Pro (batch) on 2026-09-04.
About the two models
Anthropic: Claude Opus 4.7
Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...
Full Anthropic: Claude Opus 4.7 specs →OpenAI: GPT-6 Astra Pro (batch)
GPT-6 Astra Pro is the same underlying model as [GPT-6 Astra](https://openrouter.ai/openai/gpt-6-astra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...
Full OpenAI: GPT-6 Astra Pro (batch) specs →