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# BenchDash
-**A benchmarking platform for local LLMs on Ollama** — auto-discover models, run structured tests, and compare accuracy, latency, and throughput.
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+> A benchmarking platform for local LLMs on Ollama — auto-discover models, run structured test suites, and compare accuracy, latency, and token throughput.
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+[](https://github.com/OneByJorah/BenchDash)
+[](https://github.com/OneByJorah/BenchDash)
+[](https://github.com/OneByJorah/BenchDash/stargazers)
+[](https://github.com/OneByJorah/BenchDash/commits)
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## What This Is
-Comparing local models usually means ad-hoc prompts and a stopwatch. BenchDash is a design-first platform that aims to make that repeatable: discover the models Ollama has loaded, run a fixed task suite, and rank results on accuracy, latency, and token throughput. Today the collector, dashboard, and packaging exist; the benchmark engine and scoring pipeline are planned.
+Comparing local LLMs usually means ad-hoc prompts and a stopwatch. BenchDash aims to make that repeatable: discover the models Ollama has loaded, run a fixed task suite, and rank results on accuracy, latency, and throughput. Today the system-telemetry collector, dashboard UI, Docker packaging, and install scripts exist; the benchmark engine and scoring pipeline are on the roadmap.
> [!WARNING]
-> **Pre-alpha.** The dashboard currently displays sample/demo data. The benchmark engine, scoring pipeline, JSON persistence, and backend server are not yet implemented — this scaffolding is not functional end-to-end.
+> **Pre-alpha.** The dashboard currently displays sample data. The benchmark engine, scoring pipeline, JSON persistence, and backend server are not yet implemented — the scaffolding does not run end-to-end.
## Quick Start
@@ -32,113 +24,35 @@ cd BenchDash
docker compose up -d
```
-Open **http://localhost:8081**. Run the dashboard locally with `python -m http.server 8081` instead if you prefer.
+Open **http://localhost:8081**. Or serve the dashboard directly: `python -m http.server 8081`.
## Features
-- **System telemetry collector** — gathers CPU, GPU, VRAM, CUDA, drivers, memory, and OS info in Python.
-- **Static dashboard** — standalone `index.html` with no build step; shows model comparisons, scores, and system metrics.
-- **Ollama integration (planned)** — queries the local Ollama API to enumerate models and run inference benchmarks.
-- **Configurable benchmarks** — YAML task definitions for categories, weights, and scoring.
-- **JSON persistence (planned)** — timestamped result files for historical comparison.
-- **Docker support** — Alpine image and Compose file for containerized deployment.
-- **Install scripts** — `install.sh` (Linux/macOS) and `install.ps1` (Windows).
+- **System telemetry collector** — CPU, GPU, VRAM, CUDA, drivers, memory, and OS info gathered in Python (`collector/system_info.py`).
+- **Static dashboard** — standalone `index.html` (no build step) showing model comparisons and system metrics.
+- **Ollama integration (planned)** — enumerate local models via the Ollama API and run inference benchmarks.
+- **Configurable benchmark tasks** — YAML definitions for categories, weights, and scoring (`j1.yaml`).
+- **JSON persistence (planned)** — timestamped results for historical regression tracking.
+- **Container packaging** — Alpine image with healthcheck; `install.sh` and `install.ps1` installers.
## Architecture
+```mermaid
+%%{init: {'theme':'base','themeVariables':{'primaryColor':'#0a0a09','primaryTextColor':'#FFB300','lineColor':'#FFB300'}}}%%
+graph LR
+ A[Dashboard