Llmspeed: Preview Local LLM Performance

"Stop guessing and start feeling the speed of your future setup before you spend a dime on hardware."

Instead of buying expensive GPUs blindly using a simulator, llmspeed allows you to experience the actual perceived latency of various local Large Language Models (LLMs) across a vast array of hardware configurations.

🛠️ How the Simulation Works

The tool calculates the output velocity, often measured as tokens per second ($tps$), using the following conceptual logic:

$\text{Perceived Speed} \approx \frac{\text{Model Parameters} \times \text{Precision}}{\text{Memory Bandwidth}}$

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🖥️ Supported Hardware Profiles

The simulator covers a comprehensive range of devices, from consumer laptops to enterprise cloud clusters.

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🤖 Compatible Model Benchmarks

You can test the "feel" of these specific models:

• Qwen Series:
  • Qwen 3.5 9B
  • Qwen 3.5/3.6 35B A3B
  • Qwen 3.6/3.8 27B
  • Qwen 3.8 Flash-Next
• Gemma Series:
  • Gemma 4 12B
  • Gemma 4 26B A4B
  • Gemma 4 31B
• DeepSeek & Others:
  • DeepSeek V4 Flash & V4.1 Flash
  • Llama 3.1 8B
  • GLM-5.3 & GLM-5.3 Flash
  • GPT-OSS 20B & GPT-OSS 120B
  • Nemotron 3.5 Lightning 30B A3B

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📊 Data Integrity & Access

The estimates provided for short prompts on single devices are not random; they are grounded in real-world data:

1. Community Benchmarks: Sourced from r/LocalLLaMA, localscore.ai, and other enthusiast hubs.
2. Projections: Derived from official hardware specifications and similar existing setups.

Technical Requirements:

• JavaScript enabled in browser
• Access to the web interface

The project is fully open-source. You can find the logic and the dataset here:

# Project Repository
https://github.com/nicorobinreal/llmspeed