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...
Tested on 20 benchmarks with 58.2% average. Top scores: Chatbot Arena Elo — Coding (1556.9%), Chatbot Arena Elo — Overall (1493.1%), OTIS Mock AIME 2024-2025 (97.8%).
Llama 3.3 70B Instruct scores 75.9 (99% as good) at $0.10/1M input · 98% cheaper
Complex terminal-based engineering tasks. Models must use command-line tools, navigate filesystems, and debug systems through shell interaction.
Real-world software engineering tasks from GitHub issues. Models must diagnose bugs and write patches that pass test suites. Human-verified subset of SWE-bench.
Unusual and adversarial machine learning challenges. Tests robustness of reasoning about edge cases in ML systems.
Abstraction and Reasoning Corpus. Tests fluid intelligence through novel visual pattern recognition puzzles. Core measure of general intelligence.
ARC-AGI 2, harder sequel to ARC. More complex abstract reasoning patterns that test generalization ability beyond training data.
Deceptively simple questions that humans find easy but AI models often get wrong. Tests common sense and reasoning gaps.
Mock AIME (American Invitational Mathematics Exam) problems from OTIS. Tests mathematical competition performance.
Original research-level math problems created by professional mathematicians. Problems are unpublished and cannot be memorized.
- Typemultimodal
- Context1.0M tokens (~500 books)
- ReleasedApr 2026
- LicenseProprietary
- StatusActive
- Cost / Message~$0.035