Anthropic's frontier flagship model built for deep reasoning, long-horizon agentic coding, and enterprise knowledge work — tops Terminal-Bench 2.0 and HLE with 1M context and adaptive thinking for the hardest tasks.
Anthropic
| Item | Specification |
|---|---|
| Input | Text, Image |
| Output | Text |
| Context | 200,000 tokens (1,000,000 in beta) |
| Max Output | 128,000 tokens |
| Vision | ✓ Supported |
| Function Calling | ✓ Supported (Agent Teams, Context Compaction, MCP) |
Claude Opus 4.6 is Anthropic's frontier flagship model, released on February 5, 2026 and available via the Claude API as claude-opus-4-6. It is the first Opus-class model to ship a 1M-token context window (beta) and the first Claude model with Adaptive Thinking plus four effort levels (low / medium / high / max), producing up to 128K output tokens.
Opus 4.6's defining breakthrough is turning frontier reasoning into sustained, reliable long-horizon execution. It tops Terminal-Bench 2.0 (65.4%), Humanity's Last Exam (53.0% with tools), ARC-AGI-2 (69.17%), ARC-AGI-1 (94.00%), and BrowseComp (84.0%); it finishes Vending-Bench 2's year-long simulation with a final balance of $8,017 (well above Gemini 3 Pro's prior SOTA); and on MRCR v2 8-needle 1M retrieval it scores 76% versus Sonnet 4.5's 18.5%. The release also introduces Agent Teams in Claude Code (parallel multi-agent collaboration), Context Compaction on the API, a major Claude in Excel upgrade, and a Claude in PowerPoint research preview — a full lift for enterprise workflows.
| Feature | Benefit |
|---|---|
| First 1M Context in the Opus Tier | Frontier-grade reasoning over entire codebases, hundreds of contracts, or full research corpora — no RAG plumbing required |
| Adaptive Thinking + Effort Levels | Model auto-tunes reasoning depth and developers get four explicit dials for quality/latency/cost trade-offs |
| Context Compaction (API) | Automatic context summarization lets very long agentic runs continue beyond raw token limits |
| Agent Teams Orchestration | Multiple Claude agents run in parallel inside Claude Code, accelerating large-scale and read-heavy engineering |
| Sustained Coherence | Vending-Bench 2 final balance of $8,017 demonstrates strategic planning and self-correction across thousands of decisions |
| Anthropic Safety & Alignment | Automated audits show low rates of deception, sycophancy, and delusion reinforcement — capability gains without safety regressions |
| Dimension | Rating | Notes |
|---|---|---|
| Reasoning | Top-tier | Leads HLE, ARC-AGI-2, and BigLaw Bench — undisputed frontier expert reasoning |
| Coding | Top-tier | #1 on Terminal-Bench 2.0; SWE-Bench Verified 80.8%; strongest at complex cross-file refactors |
| Creative Writing | Top-tier | Anthropic's signature voice with strong pacing, restraint, and cultural depth |
| Multimodal | Strong | Text + image input; no native video/audio (later improved in Opus 4.7) |
| Response Speed | Moderate | Flagship priced for depth over latency; Low effort mode trades reasoning for speed |
| Context Window | Huge | 200K default and 1M beta; MRCR long-context retrieval is best-in-class among contemporary models |
Our pricing is based on image and text token usage. The final cost depends on the tokens consumed.
| Token Type | LinkAI Price | Official Price |
|---|---|---|
| Input | $3.75 / 1M tokens | $5 / 1M tokens |
| Cached input | $0.375 / 1M tokens | $0.5 / 1M tokens |
| Cache write (5 minutes) | $4.6875 / 1M tokens | $6.25 / 1M tokens |
| Cache write (1 hour) | $7.5 / 1M tokens | $10 / 1M tokens |
| Output | $18.75 / 1M tokens | $25 / 1M tokens |