InternLM2 7B
InternLM2 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
- InternLM2
- Released
- 2024-01-12
- Parameters
- 7B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2023-08
- Specialization
- general
- Training
- finetuned
About
InternLM2 7B, developed by the Shanghai Artificial Intelligence Laboratory, is a large language model with 7 billion parameters, designed for a variety of natural language processing tasks. It excels in long-context understanding, capable of handling up to 200,000 characters, and demonstrates strong reasoning and math skills. The model incorporates a code interpreter, showing proficiency in programming and data analysis tasks, and is optimized for conversational interactions through advanced techniques like reinforcement learning from human feedback. Built on the transformer architecture with Grouped-Query Attention (GQA) for efficient long-sequence processing, it was trained on a diverse dataset including text, code, and long-context data. Despite its strengths, users should note potential limitations such as bias and unexpected outputs.
InternLM2 7B is a model in the InternLM2 family. No headline benchmark score is tracked for InternLM2 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.