Anthropic: Claude Opus 4.6
Chatanthropic/claude-opus-4.6Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective for large codebases, complex refactors, and multi-step debugging that unfolds over time. The model shows deeper contextual understanding, stronger problem decomposition, and greater reliability on hard engineering tasks than prior generations.Beyond coding, Opus 4.6 excels at sustained knowledge work. It produces near-production-ready documents, plans, and analyses in a single pass, and maintains coherence across very long outputs and extended sessions. This makes it a strong default for tasks that require persistence, judgment, and follow-through, such as technical design, migration planning, and end-to-end project execution.
Providers
/v1/chat/completions/v1/responsesCode Examples
import anthropicclient = anthropic.Anthropic(base_url="https://api.ofox.io/anthropic",api_key="YOUR_OFOX_API_KEY",)message = client.messages.create(model="anthropic/claude-opus-4.6",max_tokens=1024,messages=[{"role": "user", "content": "Hello!"}],)print(message.content[0].text)
Uptime & Status
Benchmarks
Anthropic: Claude Opus 4.6 scores 1498 in the Overall category of the LMArena text leaderboard (style control), ranking #4 of 374 models based on 63,487 human preference votes (updated 2026-07-12).
| Category | Arena Score | 95% CI | Rank | Votes |
|---|---|---|---|---|
| Overall | 1494–1501 | #4 of 374 | 63,487 | |
| Hard Prompts | 1523–1532 | #3 of 374 | 40,530 | |
| Coding | 1542–1554 | #5 of 369 | 17,517 | |
| Math | 1493–1514 | #5 of 362 | 3,537 | |
| Creative Writing | 1471–1485 | #7 of 372 | 10,341 | |
| Instruction Following | 1494–1505 | #4 of 374 | 20,410 | |
| Chinese | 1536–1559 | #3 of 344 | 3,242 |
Source: LMArena · CC BY 4.0 · Updated 2026-07-12 · Methodology ↗ · Ranks compare models within each category of the LMArena text leaderboard (style control). Scores come from third-party human preference evaluations, not from OFOX.