Sold by: Trillion Labs
Deployed on AWS
A 16B Mixture-of-Experts reasoning LLM (about 3B active) with step-by-step reasoning output, 32K context, and an OpenAI-compatible chat API.
Overview
Gravity-16B-A3B-Preview is a Mixture-of-Experts (MoE) large language model from Trillion Labs, built to deliver strong reasoning and generation quality at a fraction of the inference cost of comparable dense models. It has 16 billion total parameters but activates only about 3 billion per token, routing each token through a small subset of expert networks. This keeps latency and GPU cost low while preserving the breadth of a much larger model.
The model generates explicit step-by-step reasoning before its final answer, which improves reliability on analytical and multi-step tasks, and it supports a 32,768-token context window for long documents and conversations. It performs strongly in both English and Korean, making it well suited to multilingual and Korea-focused applications.
Gravity exposes a standard OpenAI-compatible chat-completions API, so existing OpenAI client libraries and tooling work without code changes. Deploy it as a real-time Amazon SageMaker endpoint for interactive applications, or run batch transform jobs to process large datasets offline. Target users: developers and enterprises building reasoning, chat, agentic, or content-generation applications, including bilingual English and Korean use cases.
Highlights
- Cost-efficient MoE: only about 3B of 16B parameters activate per token, delivering high-quality output at lower GPU cost and latency than dense models of comparable capability.
- Built-in reasoning: produces explicit step-by-step reasoning before its final answer, improving reliability on multi-step and analytical tasks.
Details
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Latest version
Deployed on AWS
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Public Release
Additional details
Inputs
- Summary
POST to /invocations with Content-Type application/json. Body is an OpenAI chat-completions object: model (must be Gravity-16B-A3B-Preview), messages array (roles system, user, assistant), optional max_tokens, temperature, top_p, stop.
- Input MIME type
- application/json
{
"model": "Gravity-16B-A3B-Preview",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is the capital of South Korea? Answer in one sentence."}
],
"max_tokens": 512,
"temperature": 0.7,
"top_p": 0.9
}
{"model":"Gravity-16B-A3B-Preview","messages":[{"role":"user","content":"Summarize: ..."}],"max_tokens":256}
{"model":"Gravity-16B-A3B-Preview","messages":[{"role":"user","content":"Translate to Korean: Hello"}],"max_tokens":128}
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