smallbench 0.2.28

Small Benchmarks for LM Agents

SmallBench

Small, simple agent task environments for training and evaluation.

Designed to challenge a broad spectrum of lm-agent abilities.

Spinning Up - Use

uv add smallbench

or

pip install smallbench

Spinning Up - Dev

uv venv smallbench-dev
source smallbench-dev/bin/activate
uv sync
uv run ruff format .

Easy Benchmarks

BigCodeBench - Agent Harness

This benchmark provides a stateful environment for lm-based agents to solve coding problems from the BigCodeBench dataset. Agents are given a scratchpad (soon), a way to prepare and use unit tests, editing handlers, and a way to submit their solution.

Please see the BigCodeBench page for more information about the underlying dataset.

Get Started

Local

add GROQ_API_KEY and any other API keys supported by the apropos-ai library to the .env file.

• Note: Groq, Google, and possibly other providers offer free tiers.

If you use a Docker backend, ensure you have the Docker app running. If you use Modal, please add all necessary credentials.

Then, run the test script:

uv run python -m src.smallbench.benchmarks.bcb_a.test

Colab

Check out the Colab if you prefer to run the benchmark in the cloud.

Medium Benchmarks

TBD

Hard Benchmarks

TBD

Difficult Benchmarks

TBD

Scores

BigCodeBench - Agent Harness (ReAct)

LM	Number Correct - Train	Number Correct - Test	Sample Size	Avg. Cost Per Run
gpt-4o-mini-2024-07-18-ft*	???	21	100	$0.006
gpt-4o-2024-08-06	17	18	100	$0.057
gpt-4o-mini-2024-07-18-ft**	???	13	100	$0.006
deepseek-v2.5	12	???	100	$0.0029
gpt-4o-mini-2024-07-18	12	8	100	$0.003
gemini-1.5-flash-latest	6	7	100	$0.0018

• "*" fine-tuned on a minimal subset (<500k tokens) of trajectories using a variation of the Filtered Behavioral Cloning approach (2024-09-17).
• "**" fine-tuned on a minimal subset (<500k tokens) of trajectories using a variation of the Filtered Behavioral Cloning approach (2024-09-08).

Animation credits: ZZ