Anthropic / anthropic/claude-sonnet-5
Claude Sonnet 5 - access through LLMTR
Previous-generation Sonnet model 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. Claude Sonnet 5.5 is the current Sonnet for new work.
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