Story
Two different tricks for fast LLM inference
1 report
1 website
1 discussion
Latest report
Overview
Anthropic's fast mode enables up to 2.5 times the token processing speed, achieving around 170 tokens per second. OpenAI's fast mode surpasses this with over 1000 tokens per second, making it six times faster than Anthropic's offering.
Summary from seangoedecke.com.
Reports
One report so far. Additional coverage will appear here when it is linked to this story.
seangoedecke.com
Two different tricks for fast LLM inference
Read report →
Community reactions
Each reaction summarizes sampled comments from the linked discussion.
Hacker News · seangoedecke.com
Hacker News discussion ↗
Historical count: 5 · 5 saved in sample · Historical sample
Analysis ready
Read this discussion’s reaction
Based on 5 sampled comments from this thread. Analyzed 2026-02-15.
- Praise: The potential for the OpenAI-Cerebras partnership to scale chips could revolutionize AI performance, enabling faster models like Codex-5.3 with fewer errors, enhancing user experience.
- Praise: In-memory inference using large SRAM chips could significantly reduce latency, making real-time applications like voice AI more natural and responsive, which is crucial for user engagement.
- Praise: The innovative approach of parallel distill and refine in Anthropic's fast mode suggests a smarter, more efficient method for handling complex problems while maintaining speed.
- Concern: The limitation of current chips, such as Cerebras' 44GB SRAM, raises concerns about their ability to handle larger models like GPT-5.3, potentially hindering advancements in AI capabilities.
- Concern: The trade-off between speed and accuracy, where increasing speed by 6x could lead to 20% more mistakes, highlights a significant challenge in optimizing AI performance for practical use.