How fast is 10 tokens per second really?

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Summary

Simon Willison explores the practical meaning of 10 tokens per second speed for large language models, offering context on how fast that feels and its implications for usability.

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Cached at: 05/20/26, 06:38 PM

# How fast is 10 tokens per second really? Source: [https://simonwillison.net/2026/May/20/tokens-per-second/](https://simonwillison.net/2026/May/20/tokens-per-second/) This is a**link post**by Simon Willison, posted on[20th May 2026](https://simonwillison.net/2026/May/20/)\. [ai2028](https://simonwillison.net/tags/ai/)[generative\-ai1795](https://simonwillison.net/tags/generative-ai/)[llms1761](https://simonwillison.net/tags/llms/) ### Monthly briefing Sponsor me for**$10/month**and get a curated email digest of the month's most important LLM developments\. Pay me to send you less\! [Sponsor & subscribe](https://github.com/sponsors/simonw/)

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The idea: on a CPU the decode speed depends on the active params per token, not the total. My objective is trying to run a 10B at 100tok/s on a mid level PC (No GPU).

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Presents the insight that CPU decode speed depends on active parameters per token, not total parameters, and proposes a 10B-parameter model using ternary weights and granular MoE to achieve high token rates on mid-level PCs. Reports sandbox measurements showing a speedup from 176 to 848 tok/s on an 8.3M model with minimal quality loss.

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