Claude Model Catalog

Only use exact model IDs listed in this file. Never guess or construct model IDs — incorrect IDs will cause API errors. Use aliases wherever available. For the latest information, WebFetch the Models Overview URL in shared/live-sources.md, or query the Models API directly (see Programmatic Model Discovery below).

Programmatic Model Discovery

For live capability data — context window, max output tokens, feature support (thinking, vision, effort, structured outputs, etc.) — query the Models API instead of relying on the cached tables below. Use this when the user asks "what's the context window for X", "does model X support vision/thinking/effort", "which models support feature Y", or wants to select a model by capability at runtime.

m = client.models.retrieve("claude-opus-4-7")
m.id                 # "claude-opus-4-7"
m.display_name       # "Claude Opus 4.7"
m.max_input_tokens   # context window (int)
m.max_tokens         # max output tokens (int)

# capabilities is an untyped nested dict — bracket access, check ["supported"] at the leaf
caps = m.capabilities
caps["image_input"]["supported"]                       # vision
caps["thinking"]["types"]["adaptive"]["supported"]     # adaptive thinking
caps["effort"]["max"]["supported"]                     # effort: max (also low/medium/high)
caps["structured_outputs"]["supported"]
caps["context_management"]["compact_20260112"]["supported"]

# filter across all models — iterate the page object directly (auto-paginates); do NOT use .data
[m for m in client.models.list()
 if m.capabilities["thinking"]["types"]["adaptive"]["supported"]
 and m.max_input_tokens >= 200_000]

Top-level fields (id, display_name, max_input_tokens, max_tokens) are typed attributes. capabilities is a dict — use bracket access, not attribute access. The API returns the full capability tree for every model with supported: true/false at each leaf, so bracket chains are safe without .get() guards. TypeScript SDK: same method names, also auto-paginates on iteration.

Raw HTTP

curl https://api.anthropic.com/v1/models/claude-opus-4-7 \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01"

{
  "id": "claude-opus-4-7",
  "display_name": "Claude Opus 4.7",
  "max_input_tokens": 200000,
  "max_tokens": 128000,
  "capabilities": {
    "image_input": {"supported": true},
    "structured_outputs": {"supported": true},
    "thinking": {"supported": true, "types": {"enabled": {"supported": false}, "adaptive": {"supported": true}}},
    "effort": {"supported": true, "low": {"supported": true}, …, "max": {"supported": true}},
    …
  }
}

Current Models (recommended)

Model Descriptions

• Claude Opus 4.7 — The most capable Claude model to date — highly autonomous, strong on long-horizon agentic work, knowledge work, vision, and memory. Adaptive thinking only; sampling parameters and budget_tokens are removed. 1M context window at standard API pricing (no long-context premium) — see shared/model-migration.md → Migrating to Opus 4.7 for breaking changes.
• Claude Opus 4.6 — Previous-generation Opus. Supports adaptive thinking (recommended), 128K max output tokens (requires streaming for large outputs). 1M context window.
• Claude Sonnet 4.6 — Our best combination of speed and intelligence. Supports adaptive thinking (recommended). 1M context window. 64K max output tokens.
• Claude Haiku 4.5 — Fastest and most cost-effective model for simple tasks.

Legacy Models (still active)

Deprecated Models (retiring soon)

Retired Models (no longer available)

Resolving User Requests

When a user asks for a model by name, use this table to find the correct model ID: