DeepSeek 7B
DeepSeek 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
- DeepSeek
- Released
- 2023-11-29
- Context
- 4k
- Parameters
- 7B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2023-05
- Specialization
- general
- Training
- finetuned
- Fine-tuning
- base
About
DeepSeek LLM 7B is an open-source model boasting 7 billion parameters, designed for multilingual tasks in English and Chinese, having trained on a substantial dataset of 2 trillion tokens 378. It follows an architecture akin to LLaMA's Multi-Head Attention, with variations tailored for different applications like the base and chat models 8. This model excels in benchmarks for language comprehension, reasoning, coding, and mathematics, though its effectiveness can vary based on task complexity and input quality 89. Prompt engineering, especially chain-of-thought prompting, enhances its performance further 1. Despite its strengths, the model's training parameters and some architectural specifics could vary, with full details not always disclosed 78. Expanding the DeepSeek LLM family, the developers have also introduced a larger 67B model and vision-language variants 810.
DeepSeek 7B is an open-source model in the DeepSeek family. The structured metadata tracks a 4k-token context window. No headline benchmark score is tracked for DeepSeek 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.