Comparing Anthropic and OpenAI's Fast Mode Approaches for LLM Inference Optimization
By
swah
Front-window bakery material. Catches the eye, delivers the goods.
Summary
Anthropic and OpenAI have both introduced "fast mode" features for their coding models, but with significant differences in approach and performance. OpenAI's fast mode offers dramatically higher speeds (over 1000 tokens per second, 15x faster than standard), while Anthropic's provides more modest gains (2.5x faster, around 170 tokens per second). However, Anthropic's key advantage is that their fast mode uses their actual Opus 4.6 model, whereas OpenAI's approach may involve different optimization techniques. The article compares these competing approaches to LLM inference optimization, highlighting the trade-offs between raw speed and model authenticity.
Key quotes
· 3 pulledAnthropic and OpenAI both recently announced 'fast mode': a way to interact with their best coding model at significantly higher speeds.
OpenAI's offers more than 1000 tokens per second (up from GPT-5.3-Codex's 65 tokens per second, so 15x). So OpenAI's fast mode is six times faster than Anthropic's.
Anthropic's big advantage is that they're serving their actual model. When you use their fast mode, you get real Opus 4.6, while when you use OpenAI...
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