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Disclaimer: These are estimates based on similar hardware configurations. Actual performance may vary due to system load, thermal throttling, and other factors.
Local LLM Tools: These estimates apply to both LM Studio and Ollama. LM Studio typically offers more optimization options, while Ollama is easier to set up. Both can run the same models with similar performance on your hardware.
For accurate results, test the models directly on your system using LM Studio or Ollama.
LLM Speed Check helps you determine which open-source AI models your device can run locally and estimates their performance speed. This tool is designed for users who want to run large language models on their own hardware using tools like LM Studio or Ollama.
How it works: The tool detects your hardware specifications (CPU cores, RAM, GPU) and matches them against a database of benchmark results from similar configurations. It then estimates how many tokens per second each model might generate on your system.
Popular models included: GPT-OSS, DeepSeek-R1, Gemma3, Qwen3, Llama 3.1/3.2, Mistral, CodeLlama, Phi-4, and more. All models are ordered by popularity based on Ollama's library.
Hardware detection: While the tool automatically detects your specs, browser limitations may not always show the full picture. You can manually override CPU cores and RAM values for more accurate results.
Use cases: Perfect for developers, researchers, and AI enthusiasts who want to run local LLMs for coding assistance, content generation, research, or experimentation without relying on cloud services.