SEA-LION 7B
SEA-LION 7B is worth evaluating for general LLM work when its provider route and context window match the workload.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 4k context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- SEA-LION
- Released
- 2024-09-01
- Context
- 4k
- Parameters
- 7B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
Cheapest of 1 route · NVIDIA NIM
About
The SEA-LION 7B model is a state-of-the-art large language model designed for the Southeast Asian region, part of the SEA-LION family. This decoder-only transformer model boasts 7 billion parameters and is based on the MPT architecture. It features a custom SEABPETokenizer with a vocabulary of 256,000 tokens, optimizing performance for Southeast Asian languages. Supporting multiple languages like English, Chinese, and Indonesian, it excels in tasks such as question answering, sentiment analysis, machine translation, and text summarization. Trained on 980 billion tokens, the model effectively captures linguistic and cultural nuances, offering strong performance and accessible open-source resources 235.
SEA-LION 7B is a model in the SEA-LION family. The structured metadata tracks a 4k-token context window. This page tracks provider routes through NVIDIA NIM. No headline benchmark score is tracked for SEA-LION 7B yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| NVIDIA NIM | - | - | ProvisionedPartial |
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.