Introducing Cerebras Inference: AI at Instant Speed

Cerebras Inference is designed to serve models with billions to trillions of parameters, splitting them at layer boundaries and mapping them to multiple CS-3 systems when they exceed the memory capacity of a single wafer. The company plans to add larger models like Llama3-405B and Mistral Large, and uses original 16-bit weights for models, which score up to 5% higher than 8-bit models. The Cerebras Inference API is available for developers to integrate, offering high performance, speed, accuracy, and cost-effectiveness.

The company emphasizes the importance of fast inference, which enables more complex AI workflows and enhances real-time LLM intelligence. Techniques like scaffolding, which require up to 100x more tokens at runtime, are only possible in real time on Cerebras hardware. Cerebras Inference, with its high-speed training and inference capabilities, sets a new standard for open LLM development and deployment.

Key takeaways:

Cerebras inference is designed to serve models from billions to trillions of parameters, with larger models such as Llama3-405B and Mistral Large to be added soon.
The system uses the original 16-bit weights released by Meta for Llama3.1 8B and 70B models, ensuring the most accurate and reliable model output.
Cerebras inference is available today via chat and API access, offering the best combination of performance, speed, accuracy and cost.
Fast inference enables more complex AI workflows and enhances real-time LLM intelligence, with new techniques like scaffolding providing over 10x performance on demanding tasks like code generation.

Introducing Cerebras Inference: AI at Instant Speed - Cerebras

Key takeaways:

Comments (0)

Newsletter