Claude Opus 5.5
- Input / 1M tokens
- $4.00
- Output / 1M tokens
- $20.00
API models · Side by side
Compare two hosted models for substantial document, coding and tool-driven tasks. Cost, context and output allowances are measurable differences; an overall quality winner needs task-specific evidence.
Both accept text, images and files. Their token rates and context allowances differ, so a large task deserves a complete request budget before it is sent repeatedly.
Compare context, supported inputs and usage costs. Highlighted rows show a difference.
| Feature | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| Input formats | file, image, text | file, image, text |
| Output formats | text | text |
| Context / position limit | 1,000,000 | 1,050,000 |
| Maximum output tokens | 128,000 | 128,000 |
| Developer features | Reasoning output, Completion limit, Output limit, Reasoning controls, Thinking effort, Response format, Stop sequences, Structured output, Tool selection, Tool calling, Response length | Reasoning output, Completion limit, Output limit, Reasoning controls, Thinking effort, Response format, Seed, Structured output, Tool selection, Tool calling, Response length |
| Cached input / 1M tokens | $0.20 | $1.00 |
| Cache write / 1M tokens | $5.00 | $12.50 |
| USD input / 1M tokens | $4.00 | $10.00 |
| USD output / 1M tokens | $20.00 | $50.00 |
| Model identifier | anthropic/claude-opus-5.5 | openai/gpt-6-astra |
Prices are in USD per million tokens. Input is what you send; output is what the model generates. Claude and ChatGPT subscriptions are billed separately.
Tools, images and additional reasoning can add charges. The examples below cover input and output tokens only.
Compare local modelsEach example uses the same token budget for both models. These are calculations, not measured workloads. Cache discounts, media, tools and extra reasoning are excluded.
| Workload | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| 1,000 short requestsPer request: 2,000 input + 500 output tokens | $18.00 | $45.00 |
| 100 document summariesPer request: 20,000 input + 1,000 output tokens | $10.00 | $25.00 |
| 10 long-document requestsPer request: 300,000 input + 2,000 output tokens | $12.40 | $61.50 |
Estimate = requests × (input tokens × input price + output tokens × output price) ÷ 1,000,000. Long-prompt rates are applied where the pricing data provides them. Real requests can use different amounts of output.
An agent may call tools, read their results and ask the model to continue. That sequence can resend substantial context several times. Budget the loop rather than one opening prompt, and set limits on unnecessary retries so the task’s total does not grow unnoticed.
A large output allowance matters for extensive reports or code generation, but allowing the maximum on every call can be costly. Separate a task that needs a full document from one that only needs the next action. Include reasoning and any extra tools in the complete operational budget.
The model does not itself supply your repository, database or tool permissions. Both require an application to provide that environment and enforce its boundaries. Compare the supported response controls with the environment you already operate, then decide whether changing the model improves a specific part of the workflow.
No. The table compares token charges for using these models in an application. Consumer subscriptions have their own prices and usage rules.
They include input and output token charges under the stated assumptions. Media, tools, additional reasoning and cache operations can add different charges.