InternVL2.5 78B vs Qwen 2.5 Coder 32B

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.

Qwen 2.5 Coder 32B: Qwen 2.5 Coder 32B Instruct is Alibaba's code-specialised model, 32.5 billion parameters (31.0 billion excluding embeddings) trained on 5.5 trillion tokens of source code, text-code grounding and synthetic data, and released under Apache 2.0. Qwen builds it for code generation, code reasoning and code repair. The published config sets a 32,768-token context by default; reaching the full 131,072 tokens requires YaRN scaling, which Qwen notes can degrade quality on shorter inputs.

Context window: InternVL2.5 78B accepts up to 32,768 tokens, Qwen 2.5 Coder 32B up to 131,072. Confirm the limit for your specific deployment channel before relying on it.