Tokenflood – simulate arbitrary loads on instruction-tuned LLMs
Hi everyone, I just released an open source load testing tool for LLMs: https://github.com/twerkmeister/tokenflood === What is it and what problems does it solve? === Tokenflood is a load testing tool for instruction-tuned LLMs hat can simulate arbitrary LLM loads in terms of prompt, prefix, and output lengths and requests per second. Instead of first collecting prompt data for different load types, you can configure the desired parameters for your load test and you are good to go. It also let's you assess the latency effects of potential prompt parameter changes before…
Tokenflood – simulate arbitrary loads on instruction-tuned LLMs launched on November 12, 2025 with 21 votes, #602 of 9,796 launches that month and more than 90% of that year's launches.
In plain words
Tokenflood is an open-source load testing tool designed for instruction-tuned large language models. It allows developers to simulate arbitrary loads by configuring prompt length, prefix length, output length, and requests per second without needing to collect real prompt data first. The tool helps teams building latency-sensitive LLM applications test self-hosted model setups and evaluate how changes to prompt parameters would affect performance before implementation.
written from the facts on this page · September 2026
From the sources
Tokenflood allows you to 1) figure out how to slash LLM latency by adjusting prompt parameters 2) assess the load curve of LLM providers before going to production with them
Tokenflood is a load testing framework for simulating arbitary loads on instruction-tuned LLMs - twerkmeister/tokenflood
In the maker’s words, at launch
Hi everyone, I just released an open source load testing tool for LLMs: https://github.com/twerkmeister/tokenflood === What is it and what problems does it solve? === Tokenflood is a load testing tool for instruction-tuned LLMs hat can simulate arbitrary LLM loads in terms of prompt, prefix, and…
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