Llama 3.1 405B on Cerebras is by far the fastest frontier model in the world

The race for faster and more efficient AI language model processing has reached a new milestone with Cerebras achieving unprecedented speeds for Meta’s Llama 3.1 405B model, marking a significant advancement in frontier AI performance.

Record-breaking performance: Cerebras has achieved a processing speed of 969 tokens per second with Llama 3.1 405B, surpassing previous limitations of frontier models.

• The speed represents a 12x improvement over GPT-4o and 18x faster than Claude 3.5 Sonnet
• Time-to-first-token latency has been reduced to just 240 milliseconds, significantly improving user experience
• The system supports a 128K context length while maintaining full model accuracy with 16-bit weights

Technical specifications and pricing: Cerebras Inference has established new benchmarks across multiple performance metrics while offering competitive pricing.

• The service will be generally available in Q1 2025
• Pricing is set at $6 per million input tokens and $12 per million output tokens, 20% lower than major cloud providers
• Performance remains strong even with extended input prompts of 100,000 tokens, achieving 539 tokens per second

Competitive landscape: The breakthrough addresses a longstanding challenge in the AI industry where developers had to choose between speed and model sophistication.

• Previous GPU, ASIC, and cloud solutions for frontier models like GPT-4o and Claude 3.5 Sonnet never exceeded 200 tokens per second
• Cerebras’s performance is 8x faster than SambaNova and 75x faster than AWS
• The system is the only non-GPU vendor to complete long-context benchmarks successfully

Real-world implications: The increased processing speed and reduced latency have significant practical applications.

• Customers switching from GPT-4 report a 75% reduction in total latency
• The improvements particularly benefit voice and video AI applications requiring real-time interaction
• The system can generate entire pages of text, code, and mathematical content rapidly

Future trajectory: The integration of open-source models with advanced inference technology suggests a shifting landscape in AI deployment.

• Llama 3.1 405B’s performance on Cerebras demonstrates the potential of open-source AI models
• The platform’s success with voice, video, and reasoning applications indicates broader applications for low-latency AI processing
• Customer trials are currently underway, suggesting imminent real-world implementation and validation

Looking ahead: While these improvements represent significant technical achievements, the true test will be the adoption and integration of this technology in practical applications, particularly in scenarios where real-time processing is crucial for user experience and functionality.