MetriLLM

# 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. - Ollama: ollama.com, then `ollama serve`
4. - LM Studio: lmstudio.ai, load a model and start the server
5. MetriLLM CLI — install globally:

```bash npm install -g metrillm ```

Usage

List available models

```bash ollama list ```

Run a full benchmark

```bash 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)

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

Skips quality evaluation — measures speed and memory only.

View previous results

```bash ls ~/.metrillm/results/ ```

Read any JSON file to see full benchmark details.

Share to the public leaderboard

```bash 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

| Verdict | Score | Meaning | |---|---|---| | EXCELLENT | >= 80 | Fast and accurate — great fit | | GOOD | >= 60 | Solid — suitable for most tasks | | MARGINAL | >= 40 | Usable but with tradeoffs | | NOT RECOMMENDED | < 40 | Too 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