InternLM XComposer2 4KHD 7B
InternLM XComposer2 4KHD 7B has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- InternLM-XComposer2
- Released
- 2024-04-09
- Parameters
- 7B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2023-08
- Specialization
- general
- Training
- finetuned
About
InternLM-XComposer2-4KHD-7B is a large vision-language model designed to understand high-resolution images up to 4K HD (3840 x 1600 pixels). Built on the InternLM2 architecture, it significantly improves over previous models with its dynamic image partitioning approach that divides images into smaller patches while maintaining the original aspect ratio. This enables it to handle fine-grained visual details, making it ideal for tasks like image captioning, visual question answering, and high-resolution OCR. The model features a lightweight Vision Encoder and the InternLM2-7B language model, using Partial LoRA for efficient alignment. With capabilities that extend to complex applications such as automated marketing or e-commerce image captioning, it competes effectively against models like GPT-4V and Gemini Pro, although it requires substantial GPU resources, with RAM usage reported near 80GB.
InternLM XComposer2 4KHD 7B is a model in the InternLM-XComposer2 family. No headline benchmark score is tracked for InternLM XComposer2 4KHD 7B yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.