# LLM Algorithmic Benchmark

This repository contains a suite of difficult algorithmic tests to benchmark the code generation capabilities of various Large Language Models.

The tests are run automatically via GitHub Actions, and the results are updated in this README.

## Configuration

Set the percentage of tests to run during the benchmark. 100% runs all tests.

<!-- CONFIG_START -->
RUN_PERCENTAGE: 25
<!-- CONFIG_END -->

## Models Under Test

The following models are included in the benchmark run.

<!-- MODELS_START -->
google/gemini-2.5-pro
anthropic/claude-sonnet-4.5
openai/gpt-5-codex
<!-- MODELS_END -->

## Benchmark Results

The list below shows the pass/fail status and execution time for each model on each test.

<!-- RESULTS_START -->
**google/gemini-2.5-pro**
- 1_dijkstra: ❌ Fail (0.213s)
- 2_convex_hull: ⚪ Not Run
- 3_lis: ⚪ Not Run
- 4_determinant: ⚪ Not Run

**anthropic/claude-sonnet-4.5**
- 1_dijkstra: ❌ Fail (0.189s)
- 2_convex_hull: ⚪ Not Run
- 3_lis: ⚪ Not Run
- 4_determinant: ⚪ Not Run

**openai/gpt-5-codex**
- 1_dijkstra: ❌ Fail (0.245s)
- 2_convex_hull: ⚪ Not Run
- 3_lis: ⚪ Not Run
- 4_determinant: ⚪ Not Run
<!-- RESULTS_END -->