Claude Opus 4.7 performance data on Rival is based on blind head-to-head community voting. All vote data is part of Rival's open dataset of 21,000+ human preference judgments across 200+ AI models. Model responses are curated from 53 challenges.
These are the models that show up when Claude Opus 4.7 doesn't. Or when it does, but you want a second opinion. Which is healthy.
Claude Opus 4.7 performance data on Rival is based on blind head-to-head community voting. All vote data is part of Rival's open dataset of 21,000+ human preference judgments across 200+ AI models. Model responses are curated from 53 challenges.
These are the models that show up when Claude Opus 4.7 doesn't. Or when it does, but you want a second opinion. Which is healthy.
Anthropic's next-generation Opus model, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on complex, multi-step tasks and more reliable agentic execution across extended workflows. Especially effective for asynchronous agent pipelines where tasks unfold over time - large codebases, multi-stage debugging, and end-to-end project orchestration. Beyond coding, brings improved knowledge work capabilities from drafting documents and building presentations to analyzing data. Maintains coherence across very long outputs and extended sessions, making it a strong default for tasks that require persistence, judgment, and follow-through.
Use Claude Opus 4.7 in your applications via the OpenRouter API. Copy the code below to get started.
import requests
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions" ,
headers={
"Authorization""Bearer $OPENROUTER_API_KEY" : ,
"Content-Type""application/json" :
},
json={
"model""anthropic/claude-opus-4.7" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
Principled executor that balances thoroughness with pragmatism. Engages moral complexity honestly without imposing judgment. Respects constraints absolutely while finding creative space within them.
Maps the full problem space before committing to a path, then executes with sustained focus across extended workflows. Comfortable holding multiple threads over long sessions. Builds solutions that anticipate downstream consequences rather than optimizing for immediate output.
Unique words vs. total words. Higher = richer vocabulary.
Average words per sentence.
"Might", "perhaps", "arguably" per 100 words.
**Bold** markers per 1,000 characters.
Bullet and numbered list items per 1,000 characters.
Markdown headings per 1,000 characters.
Emoji per 1,000 characters.
"However", "moreover", "furthermore" per 100 words.
53 outputs from Claude Opus 4.7
Try Claude Opus 4.7
Anthropic's next-generation Opus model, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on complex, multi-step tasks and more reliable agentic execution across extended workflows. Especially effective for asynchronous agent pipelines where tasks unfold over time - large codebases, multi-stage debugging, and end-to-end project orchestration. Beyond coding, brings improved knowledge work capabilities from drafting documents and building presentations to analyzing data. Maintains coherence across very long outputs and extended sessions, making it a strong default for tasks that require persistence, judgment, and follow-through.
Use Claude Opus 4.7 in your applications via the OpenRouter API. Copy the code below to get started.
import requests
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions" ,
headers={
"Authorization""Bearer $OPENROUTER_API_KEY" : ,
"Content-Type""application/json" :
},
json={
"model""anthropic/claude-opus-4.7" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
Principled executor that balances thoroughness with pragmatism. Engages moral complexity honestly without imposing judgment. Respects constraints absolutely while finding creative space within them.
Maps the full problem space before committing to a path, then executes with sustained focus across extended workflows. Comfortable holding multiple threads over long sessions. Builds solutions that anticipate downstream consequences rather than optimizing for immediate output.
Unique words vs. total words. Higher = richer vocabulary.
Average words per sentence.
"Might", "perhaps", "arguably" per 100 words.
**Bold** markers per 1,000 characters.
Bullet and numbered list items per 1,000 characters.
Markdown headings per 1,000 characters.
Emoji per 1,000 characters.
"However", "moreover", "furthermore" per 100 words.
53 outputs from Claude Opus 4.7
Try Claude Opus 4.7