Unsloth AI
About Unsloth AI
Unsloth AI is a San Francisco–based company on a mission to make custom AI accessible to the widest possible audience. It fixes critical bugs in large language models such as Gemma, Llama, and Phi-4, and conducts open-source reinforcement learning and fine-tuning for LLMs. Backed by Y Combinator in the S24 cohort, it is supported by notable investors including Logan Kilpatrick, Cliff Obrecht, and Jon Oringer. The company has built a strong community, with 29,000+ GitHub stars and more than 8 million monthly downloads on Hugging Face. Its technology is adopted by Canva, LinkedIn, NASA, NVIDIA, and other organizations.
Company at a glance
Location
Life at Unsloth AI
Frequently asked questions
Companies similar to Unsloth AI
Ambi is building the interface for the AI era - software and hardware that move at the speed of thought. We're creating a living memory system that turns conversations, meetings, and daily signals into one connected knowledge base, across phone, watch, and desktop. Backed and early-stage, headquartered in San Francisco with hybrid flexibility - this is a ground-floor seat on category-defining hardware.
Arbio, headquartered in Berlin, Germany, is building an AI-native property management platform for short-term rentals across Europe. It currently manages over 1,000 apartments and operates real properties in Berlin, Hamburg, Vienna, and Leipzig, with plans to expand to additional European cities. The company has raised a $36 million Series A funding and maintains an engineering team of five engineers. Arbio’s platform uses AI to observe, decide, and act on real-world property operations with humans in the loop, enabling AI-assisted management of short-term rental properties across Europe.
Arga Labs provides isolated sandbox environments equipped with API twins of third-party services, enabling developers and organizations to safely test and train AI agents without risking their production systems. By offering a controlled testing ground that mirrors real-world APIs, the company allows teams to experiment with AI implementations, validate workflows, and refine agent behavior in a risk-free setting. This approach addresses a critical need in AI development, where testing in live environments can introduce costly errors or security vulnerabilities.