SiliconFlow vs Together AI Inference

SiliconFlow

Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice.

Together AI Inference

A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, and shared capacity has no fixed throughput guarantee. Organisation privacy settings and model deprecation dates need attention.

SiliconFlow

1. Set the OpenAI client's base URL to https://api.siliconflow.com/v1, or the Anthropic client's to https://api.siliconflow.com/, and send the key as a Bearer token
2. Take model ids from the model pages or GET /v1/models, not from the OpenAPI enum or the function calling guide, which list removed models
3. Check the model field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models
4. Use response_format of json_object only where the model page says JSON Mode is supported, and keep max_tokens about 10,000 below the context length
5. Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash

Together AI Inference

1. Create a project-scoped key and set TOGETHER_API_KEY. Avoid deprecated legacy keys.
2. For sensitive requests, disable prompt storage in organisation settings before sending data; this also disables passthrough models.
3. Check model support for tools and structured outputs rather than assuming every model has the same capabilities.
4. Back off on 429 and 503 responses. Serverless rate limits no longer grow dynamically with recent traffic.
5. Check the deprecation schedule before choosing a model; Llama 3.3 70B Turbo is scheduled to leave serverless on 22 October 2026.