Simon Willison’s Weblog

S1: The $6 R1 Competitor? Tim Kellogg shares his notes on a new paper, s1: Simple test-time scaling, which describes an inference-scaling model fine-tuned on top of Qwen2.5-32B-Instruct for just $6 - the cost for 26 minutes on 16 NVIDIA H100 GPUs.

Tim highlight the most exciting result:

After sifting their dataset of 56K examples down to just the best 1K, they found that the core 1K is all that's needed to achieve o1-preview performance on a 32B model.

The paper describes a technique called "Budget forcing":

To enforce a minimum, we suppress the generation of the end-of-thinking token delimiter and optionally append the string “Wait” to the model’s current reasoning trace to encourage the model to reflect on its current generation

That's the same trick Theia Vogel described a few weeks ago.

Here's the s1-32B model on Hugging Face. I found a GGUF version of it at brittlewis12/s1-32B-GGUF, which I ran using Ollama like so:

ollama run hf.co/brittlewis12/s1-32B-GGUF:Q4_0

I also found those 1,000 samples on Hugging Face in the simplescaling/s1K data repository there.

I used DuckDB to convert the parquet file to CSV (and turn one VARCHAR[] column into JSON):

COPY (
    SELECT 
      solution,
      question,
      cot_type,
      source_type,
      metadata,
      cot,
      json_array(thinking_trajectories) as thinking_trajectories,
      attempt
    FROM 's1k-00001.parquet'
) TO 'output.csv' (HEADER, DELIMITER ',');

Then I loaded that CSV into sqlite-utils so I could use the convert command to turn a Python data structure into JSON using json.dumps() and eval():

# Load into SQLite
sqlite-utils insert s1k.db s1k output.csv --csv
# Fix that column
sqlite-utils convert s1k.db s1u metadata 'json.dumps(eval(value))' --import json
# Dump that back out to CSV
sqlite-utils rows s1k.db s1k --csv > s1k.csv

Here's that CSV in a Gist, which means I can load it into Datasette Lite.

It really is a tiny amount of training data. It's mostly math and science, but there are also 15 cryptic crossword examples.