Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $1.00 |
| Output tokens | $2.00 |
Capabilities
About Smaug 72B
Smaug 72B is a large language model (LLM) developed by Abacus AI, distinguished as the first open-source model to exceed an average score of 80% on the Hugging Face Open LLM Leaderboard. It excels in various tasks, outperforming even some proprietary models like GPT-3.5 in specific benchmarks. The model is based on the Qwen-72B and fine-tuned using a novel DPO-Positive (DPOP) technique, leveraging datasets such as ARC, HellaSwag, and MetaMath. Its capabilities include question answering, text translation, and poem generation, with notable performance in reasoning and math tasks. Despite its strengths, Smaug 72B faces limitations such as dataset contamination and challenges in complex contextual understanding. Its open-source nature allows for community-based enhancements and it supports a 32k context length for processing longer inputs.