Toronto-based chip startup Taalas announced on Thursday that it has completed a $169 million funding round and revealed the development of a new chip that runs artificial intelligence applications faster and at a lower cost than conventional solutions.

This announcement comes just weeks after NVIDIA secured a $20 billion intellectual property licensing deal with chip startup Groq ahead of Christmas, reigniting market interest in a group of startups and technologies focused on specific aspects of AI inference. AI inference refers to the process where AI models, such as OpenAI's ChatGPT, respond to user queries.

Taalas's chip design approach involves etching parts of AI model architectures directly onto silicon, creating customized chips optimized for specific models like Meta's lightweight Llama. These specialized silicon chips are paired with substantial amounts of high-speed, though costlier, on-chip SRAM memory, following a design philosophy similar to Groq's.

However, Taalas's key advantage lies in its tailored design for each individual model.

"This hardware-level customization is part of what gives us our speed advantage," CEO Ljubisa Bajic stated in an interview with Reuters.

Bajic explained that the startup completes approximately 100 layers of near-full chip fabrication before making final customizations on two metal layers. Taalas's chips are manufactured by TSMC, with production for model-specific chips completing in approximately two months.

In comparison, production cycles for AI processors like NVIDIA's Blackwell typically span about six months.

Taalas confirmed it can currently produce chips capable of running lightweight AI models and plans to launch processors supporting top-tier large models like GPT-5.2 by year-end.

Groq's first-generation processor also employs a high-SRAM design approach, while two other startups—Cerebras, which formed a cloud computing partnership with OpenAI in January, and D-Matrix—have adopted similar solutions.