MetriLLM

v0.2.11

Find the best local LLM for your machine. Tests speed, quality and RAM fit, then tells you if a model is worth running on your hardware.

0· 433· 11 versions· 0 current· 0 all-time· Updated 22h ago· MIT-0

MetriLLM — Find the Best LLM for Your Hardware

Test any local model and get a clear verdict: is it worth running on your machine?

Prerequisites

  1. Node.js 20+ — check with node -v
  2. Ollama or LM Studio installed and running
  3. MetriLLM CLI — install globally:
npm install -g metrillm

Usage

List available models

ollama list

Run a full benchmark

metrillm bench --model $ARGUMENTS --json

This measures:

  • Performance: tokens/second, time to first token, memory usage
  • Quality: reasoning, math, coding, instruction following, structured output, multilingual
  • Fitness verdict: EXCELLENT / GOOD / MARGINAL / NOT RECOMMENDED

Performance-only benchmark (faster)

metrillm bench --model $ARGUMENTS --perf-only --json

Skips quality evaluation — measures speed and memory only.

View previous results

ls ~/.metrillm/results/

Read any JSON file to see full benchmark details.

Share to the public leaderboard

metrillm bench --model $ARGUMENTS --share

Uploads your result to the MetriLLM community leaderboard — an open, community-driven ranking of local LLM performance across real hardware. Compare your results with others and help the community find the best models for every setup. Shared data includes: model name, scores, hardware specs (CPU, RAM, GPU). No personal data is sent.

Interpreting Results

VerdictScoreMeaning
EXCELLENT>= 80Fast and accurate — great fit
GOOD>= 60Solid — suitable for most tasks
MARGINAL>= 40Usable but with tradeoffs
NOT RECOMMENDED< 40Too slow or inaccurate

Key metrics to highlight:

  • tokensPerSecond > 30 = good for interactive use
  • ttft < 500ms = responsive
  • memoryUsedGB vs available RAM = will it fit?

Tips

  • Use --perf-only for quick tests
  • Close GPU-intensive apps before benchmarking
  • Benchmark duration varies depending on model speed and response length

Open Source

MetriLLM is free and open source (Apache 2.0). Contributions, issues, and feedback are welcome: github.com/MetriLLM/metrillm

Version tags

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