Text Embedding 3 Large vs InternVL2.5 78B

Overview

InternVL2.5 78B: InternVL2.5 78B is OpenGVLab's multimodal model in the ViT-MLP-LLM configuration, pairing the InternViT-6B-448px-V2.5 vision encoder with Qwen2.5-72B-Instruct as its language model for roughly 78 billion parameters in total. It keeps InternVL 2.0's architecture and advances instead through training and test-time strategy and a larger, filtered data mixture. The project is released under the MIT licence, while the Qwen2.5-72B-Instruct component it embeds carries the Qwen licence.

Text Embedding 3 Large: Text Embedding 3 Large is OpenAI's larger third-generation embedding model, returning 3,072-dimension vectors from inputs of up to 8,192 tokens. Its dimensions parameter shortens the vector at creation time without, as OpenAI puts it, the embedding losing its concept-representing properties, which lets a retrieval system trade index size against accuracy without changing models. Shortening at creation is preferred to truncating afterwards, which requires re-normalising the vector.

Context window: InternVL2.5 78B accepts up to 32,768 tokens, Text Embedding 3 Large up to 8,191. Confirm the limit for your specific deployment channel before relying on it.