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Description
Tülu 3 is a cutting-edge language model created by the Allen Institute for AI (Ai2) that aims to improve proficiency in fields like knowledge, reasoning, mathematics, coding, and safety. It is based on the Llama 3 Base and undergoes a detailed four-stage post-training regimen: careful prompt curation and synthesis, supervised fine-tuning on a wide array of prompts and completions, preference tuning utilizing both off- and on-policy data, and a unique reinforcement learning strategy that enhances targeted skills through measurable rewards. Notably, this open-source model sets itself apart by ensuring complete transparency, offering access to its training data, code, and evaluation tools, thus bridging the performance divide between open and proprietary fine-tuning techniques. Performance assessments reveal that Tülu 3 surpasses other models with comparable sizes, like Llama 3.1-Instruct and Qwen2.5-Instruct, across an array of benchmarks, highlighting its effectiveness. The continuous development of Tülu 3 signifies the commitment to advancing AI capabilities while promoting an open and accessible approach to technology.
Description
Distil Labs enhances AI performance by substituting costly calls to advanced models with tailored small language models designed for specific tasks while ensuring the quality standards are upheld. By monitoring real production traffic and gathering traces from current LLM requests, it constructs an evaluation set to gain insights into actual workload behavior. Following this, the company creates and verifies synthetic training data, aligns the data distribution with the intended workload, and engages in supervised fine-tuning alongside reinforcement learning. The model is then quantized, and an optimized endpoint is established. The outcomes are systematically assessed against the existing model concerning accuracy, latency, and efficiency, providing teams with data to determine when to increase traffic. Ultimately, the OpenAI-compatible endpoint features a specialized small language model, prompt optimization, effective caching, and refined serving tailored for the specific application, ensuring maximum performance. This comprehensive approach allows organizations to maximize the potential of their AI implementations.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Baseten
Yes
BuildThatIdea
Yes
C
Yes
C#
Yes
C++
Yes
CSS
Yes
Elixir
Yes
F#
Yes
GPT-5.4 nano
No
HTML
Yes
Integrations
Baseten
No
BuildThatIdea
No
C
No
C#
No
C++
No
CSS
No
Elixir
No
F#
No
GPT-5.4 nano
Yes
HTML
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Pricing Details
$0.04 per 1M tokens
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Ai2
Founded
2014
Country
United States
Website
allenai.org/tulu
Vendor Details
Company Name
distil labs
Founded
2024
Country
Germany
Website
www.distillabs.ai/
