TokenSpeed tool visualizes local LLM speed: is 21 tokens/sec fast?
A web tool turns abstract token/second numbers into a tangible experience.
For anyone running local LLMs, performance metrics like tokens/second are objective but often meaningless without context. MikeVeerman’s new web tool, TokenSpeed, solves this by letting you actually experience how fast different rates feel across text generation, code completion, and reasoning+code tasks. You can input a specific tokens/second speed (e.g., 21 or 10) and see real-time output, making it clear whether a model is usable for interactive work.
The tool supports three modes to match your use case: plain text for chat-style generation, code for autocomplete-like speed, and reasoning+code for thought-intensive tasks. This helps you decide if dropping to a smaller model or quantizing further is worth the tradeoff. As local LLM deployments grow (Qwen, Llama, Mistral) for privacy and cost, this fills a critical gap in benchmarking. Try it free at mikeveerman.github.io/tokenspeed.
- TokenSpeed converts abstract tokens/second numbers into a subjective, real-time speed experience.
- Supports three display modes: text, code, and reasoning+code to match different local LLM use cases.
- Free web tool by MikeVeerman, useful for comparing local model performance (e.g., Qwen 3.6-27B at 21 vs 10 tokens/sec).
Why It Matters
Makes local LLM speed benchmarks actionable, helping professionals choose the right model and quantization for real-time use.