LLM Reference

SeaLLM 2 Models by Alibaba

2 models2024Up to 32k ctx

About

The SeaLLM family is a series of large language models designed to cater to Southeast Asian languages, showcasing superior multilingual capabilities. The SeaLLM-7B-v2 marks a significant advancement, effectively outperforming larger models like its predecessor and GPT-3.5 in various multilingual tasks such as world knowledge, math reasoning, and instruction following. It notably excels in the zero-shot GSM8K task, achieving state-of-the-art performance. Building on this, the SeaLLM-7B-v2.5 further enhances its proficiency in reasoning benchmarks and world knowledge. Despite these strengths, users are advised to exercise caution as the models, even with safety fine-tuning, might still produce misleading or harmful content. The recent release of SeaLLMs-v3 improves on trustworthiness and reduces hallucinations, furthering the advancement in handling non-Latin Southeast Asian languages 145.

Current Variants

Use-when guidance is derived from seed capabilities, context, release, and replacement fields.

1 in view1 retired

Use when the workload needs 32k context and 7B parameters.

2024-0732k context7B parameters

Release Timeline

1 release group
2024-07
1 current · 1 retired
SeaLLM 7B V2
32k context7B parameters
Current
SeaLLM 7B V2.5
32k context7B parameters
Archived

Specifications(2 models)

SeaLLM 2 model specifications comparison
ModelReleasedContextParameters
SeaLLM 7B V22024-0732k7B

Available From(1 provider)

Frequently Asked Questions

What is SeaLLM 2 used for?
SeaLLM 2 is used for math-heavy prompts. The family description and listed model capabilities point to those workloads as the best fit.
How does SeaLLM 2 compare to Tongyi DeepResearch?
SeaLLM 2 by Alibaba is strongest where you need math-heavy prompts, while Tongyi DeepResearch by Alibaba is the closest related family to check for adjacent model selection. SeaLLM 2 has 2 listed variants and reaches up to 32k context, while Tongyi DeepResearch reaches up to 131k context, so compare the specs and pricing tables before choosing a production model.
Which SeaLLM 2 model should I use?
If price is the main constraint, use the pricing table first because SeaLLM 2 does not have complete provider pricing in the local data. For the most capable/latest local choice, evaluate SeaLLM 7B V2 with 32k context.

Models(2)