Claude Opus 4.7
Released April 2026 as the successor to Opus 4.6, with gains concentrated on difficult software engineering tasks and long-context recall.
- Input
- $5.00 / 1M tokens
- Output
- $25.00 / 1M tokens
About $100.00 for 10M input and 2M output tokens. Estimate yours
Key Specifications
- Context window
- 1M tokens
- Max output
- 128K tokens
- Knowledge cutoff
- Inputs
- Text, Image Outputs: Text
Claude Opus 4.7 pricing by provider
| Provider | Input / 1M tokens | Output / 1M tokens | Cost at 10M in + 2M out | |
|---|---|---|---|---|
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$5.00 | $25.00 | $100.00 | View |
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$5.00 | $25.00 | $100.00 | View |
Heads up: We do our best to keep these specs & prices accurate. However, cloud costs may fluctuate based on region, usage, and other factors not listed here. These are estimates based on common setups and are for informational purposes only. Always verify current rates & exact specs with the provider before provisioning. LLM rates are base-tier, on-demand prices per 1M tokens; cached-input, batch and long-context tiers are not included.
Compare every model at this volume in the LLM cost calculator.
Capabilities
Function calling
Connect to external tools, APIs, and systems.
Structured output
Return responses in structured formats like JSON.
More from Anthropic
| Model | Context | Input / 1M | Output / 1M |
|---|---|---|---|
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1M | $5.00 | $25.00 |
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1M | $5.00 | $25.00 |
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1M | $5.00 | $25.00 |
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200K | $5.00 | $25.00 |
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1M | $3.00 | $15.00 |
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200K | $3.00 | $15.00 |
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200K | $3.00 | $15.00 |
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1M | $10.00 | $50.00 |
Models near this price
The models nearest this one by input rate, five each way, at each one's cheapest listed provider.
Frequently Asked Questions
How much does Claude Opus 4.7 cost?
Claude Opus 4.7 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens via Anthropic; all 2 providers listing it charge the same rate.
What does Claude Opus 4.7 cost for 10M input and 2M output tokens?
At Anthropic's rates, 10M input tokens and 2M output tokens cost about $100.00: $50.00 for input and $50.00 for output. Input is prompts and context, output is what the model writes back; a workload that generates more than it reads shifts the cost toward the output rate of $25.00 per 1M tokens.
Which providers offer Claude Opus 4.7?
2 providers list Claude Opus 4.7: Anthropic ($5.00 in / $25.00 out) and Replicate ($5.00 in / $25.00 out). Rates are per 1M tokens in USD, cheapest input rate first.
What is Claude Opus 4.7's context window?
Claude Opus 4.7 accepts up to 1M tokens of input per request and returns up to 128K tokens per response. The context window is the prompt plus any documents, conversation history and tool results sent with it; every token in it is billed at the input rate.
What is Claude Opus 4.7's knowledge cutoff?
Claude Opus 4.7's knowledge cutoff is January 2026: its training data runs up to that month and it has no built-in knowledge of later events.
What inputs and outputs does Claude Opus 4.7 support?
Claude Opus 4.7 accepts text and images as input and produces text. Its listed capabilities are function calling and structured output.
How does Claude Opus 4.7 compare with Claude Opus 5?
Claude Opus 4.7 and Claude Opus 5 both cost $5.00 per 1M input tokens ($25.00 vs $25.00 per 1M output tokens). Both have a 1M-token context window.
What are cheaper alternatives to Claude Opus 4.7?
Models from other creators with a lower input rate and at least Claude Opus 4.7's 1M-token context window: Kimi K3 at $3.00 per 1M input tokens (1M context), GPT-5.6 Sol at $2.50 per 1M input tokens (1M context) and GPT-5.4 at $2.50 per 1M input tokens (1M context). Rates are the cheapest listed provider for each; whether the quality holds for a given task is a separate question.
Cheaper alternatives to Claude Opus 4.7
Kimi K3
$3.00 per 1M input tokens and $15.00 per 1M output tokens via Moonshot AI, 1M-token context, by Moonshot AI.
GPT-5.6 Sol
$2.50 per 1M input tokens and $15.00 per 1M output tokens via Replicate, 1M-token context, by OpenAI.
GPT-5.4
$2.50 per 1M input tokens and $15.00 per 1M output tokens via OpenAI, 1M-token context, by OpenAI.