Anthropic / anthropic/claude-sonnet-5
Claude Sonnet 5 - access through LLMTR
Next-generation Sonnet model positioned as a drop-in upgrade from Sonnet 4.6. It is a strong fit for coding, tool-using agents, long-document analysis, and production assistants that need a high speed-to-intelligence balance, with 1M context, 128K max output, adaptive thinking by default, vision input, tool calling, and prompt cache support.
Technical specifications
| Canonical ID | anthropic/claude-sonnet-5 |
|---|---|
| Provider | Anthropic |
| Context window | 1,000,000 tokens |
| Operations | CHAT_COMPLETIONS |
| Modalities | text, image |
Pricing
An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.
| Operation | Metric | Unit | Price |
|---|---|---|---|
| CHAT_COMPLETIONS | INPUT_TEXT | PER_1M_TOKENS | $2.00 |
| CHAT_COMPLETIONS | CACHE_READ | PER_1M_TOKENS | $0.200000 |
| CHAT_COMPLETIONS | OUTPUT_TEXT | PER_1M_TOKENS | $10.00 |
| CHAT_COMPLETIONS | CACHE_WRITE | PER_1M_TOKENS | $2.50 |
| CHAT_COMPLETIONS | CACHE_WRITE | PER_1M_TOKENS | $4.00 |
Example usage
With existing OpenAI SDK flows, change only the base URL and model identifier.
curl https://llmtr.com/v1/chat/completions -H "Authorization: Bearer llmtr-your_key" -H "Content-Type: application/json" -d '{"model":"anthropic/claude-sonnet-5","messages":[{"role":"user","content":"Hello"}]}'Guides about this model
- Claude Sonnet 4.6: strong on existing systems, Sonnet 5 for new work - Claude Sonnet 4.6's catalog description draws a clear line: strong for existing systems, Sonnet 5 more current for new integrations. This article covers what concrete decisions that distinction translates into.
- Connecting Claude Code to LLMTR through the Anthropic Messages endpoint - Claude Code needs no modified build: base URL, credential and model identifier are supplied as environment variables. This guide covers model discovery, the context window warning and the unsupported fields separately.
- OpenClaw LLMTR plugin: package install and manifest walkthrough - OpenClaw does not bake the LLMTR provider into its core. It carries the integration as a package under the extensions directory with its own manifest and model catalog, and this guide unpacks both.
- Strix LLMTR setup: model prefix, dedupe and the reporting chain - Built from the real files on two separate Strix branches, this guide walks through model prefix resolution, why the dedupe model needs its own endpoint, and which Turkey-hosted rows actually support the tool calls an agent loop needs.
- Trae Agent with LLMTR: Python configuration and trajectory records - Trae Agent reaches LLMTR through a dispatching class that splits models across two client implementations. This guide walks the Python configuration, the routing decision and the fields visible in the run record.
- Setting up the LLMTR provider in OpenCompany workflows - In a workflow engine a model node builds its client from the selected credential and then resolves the model. Because LLMTR is a gateway, that resolution reads two separate sources: wire shape from the vendor, thinking from the gateway.
- Connecting OpenStory to the LLMTR gateway with a team key - OpenStory is a multi-team production platform, so the key is not a single environment variable. An LLMTR key can be entered per team, and it outranks the other providers whenever the gateway carries the requested model.
- Connecting Open WebUI to LLMTR: keeping the chat model list usable - Open WebUI treats a gateway catalog as if every entry were a chat model. This guide sets up the connection, inspects the catalog without a key, and narrows the picker to models that can actually hold a conversation.
Related models
- Claude Fable 5.1 anthropic/claude-fable-5.1
- Claude Opus 5.5 anthropic/claude-opus-5.5
- Claude Fable 5 anthropic/claude-fable-5
- Claude Opus 5 anthropic/claude-opus-5
- Claude Opus 4.8 anthropic/claude-opus-4.8
- Claude Opus 4.7 anthropic/claude-opus-4.7
- Claude Opus 4.6 anthropic/claude-opus-4.6
- Claude Opus 4.5 anthropic/claude-opus-4.5