TL;DR: For batch embeddings on DeepInfra, pass an array of strings as input in one request instead of looping one request per text. Set encoding_format to float; it is the only supported value, so requests for base64 encodings fail. Models like Qwen/Qwen3-Embedding-8B or BAAI/bge-base-en-v1.5 work through the standard OpenAI embeddings client pointed at the /v1/openai base URL.

## Fix
1. For batch embeddings on DeepInfra, pass an array of strings as input in one request instead of looping one request per text.
   Expected: this specific failure stops.
2. Set encoding_format to float; it is the only supported value, so requests for base64 encodings fail.
   Expected: this specific failure stops.

## Details
Models like Qwen/Qwen3-Embedding-8B or BAAI/bge-base-en-v1.5 work through the standard OpenAI embeddings client pointed at the /v1/openai base URL. Context: DeepInfra docs Embeddings (deepinfra/docs apis/embeddings.mdx): POST YOUR_HOST.deepinfra.com/v1/openai/embeddings takes model, input (a string or an array of strings), and encoding_format, which is float only. Batch embeddings are a plain array as input. The example uses model Qwen/Qwen3-Embedding-8B via the OpenAI SDK with base_url YOUR_HOST.deepinfra.com/v1/openai.

## When to use
You hit exactly this: DeepInfra embeddings batch with an array, encoding format is float only.

## When not to use
A different error, or the same symptom in a different tool. This page only covers the failure above.

## Compatibility
the tool named in the title (versions mentioned here: v1.5, v1).