BlueLM 7B
BlueLM 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
- Workloads that can use a 4k context window
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
- BlueLM
- Released
- 2023-11-12
- Context
- 4k
- Parameters
- 7B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
BlueLM 7B is an advanced open-source language model developed by vivo AI Lab, equipped with 7 billion parameters and based on the GPT-Neo architecture. It supports both base and chat functionalities, capable of handling up to 32K token contexts, which is advantageous for tasks requiring complex text comprehension. Trained on 2.6 trillion tokens from primarily Chinese and English sources, with additional Japanese and Korean text, it excels in tasks such as text generation, summarization, and question-answering, demonstrating strong performance in benchmarks like C-Eval and CMMLU. Though open for research and commercial use, users should be mindful of potential biases and the lack of specific safety fine-tuning.
BlueLM 7B is a model in the BlueLM family. The structured metadata tracks a 4k-token context window. No headline benchmark score is tracked for BlueLM 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.