This benchmark asks a constrained question: when two compressors receive the same long tool result and the same maximum token cap, how often does the compressed context retain an accepted answer?
It compares the Entroly 1.0.59 source candidate with the published External Baseline A
0.31.0 compress() API. It is intentionally narrower than a general model or
agent benchmark. External Baseline A’s compressed output can contain CCR pointers; this
benchmark records those pointers but does not invoke retrieval recovery. The
result therefore measures immediately visible active context, not External Baseline A’s
end-to-end CCR workflow.
20260715; development used the separate seed 20260714.o200k_base tokens (2x, 4x, 8x).qwen2.5:1.5b at the 4x cap, temperature 0 and seed 0.Distractors containing an accepted answer string are excluded. The artifact stores the complete inputs, outputs, hashes, package identities, exact configuration, achieved token ratios, target misses, latency samples, model digest, prompts, predictions, and errors.
Requested ratios are never reported as achieved compression. Both public APIs
receive up to three feedback attempts using their own target control and the
same measured o200k_base output count. A system that still exceeds the cap is
recorded as missing it; the row is not dropped.
The External Baseline A adapter declares savings_profile="agent-90",
protect_recent=0, min_tokens_to_compress=0, and the matrix target ratio.
The Entroly adapter declares the exact target budget and disables receipt
headers. Both run in isolated Python processes with user secrets removed and
network-dependent model downloads disabled.
The public win label appears only when all of these conditions pass:
p <= 0.05;Changing an output, token count, aggregate, decision, or payload hash makes the committed verifier fail.
Use an isolated External Baseline A environment. On Windows, External Baseline A 0.31.0 currently
needs an older compatible ast-grep-cli wheel because the latest wheel can
fail while creating sg.exe:
py -3.10 -m venv .venv-External Baseline A
.venv-External Baseline A\Scripts\python.exe -m pip install ast-grep-cli==0.30.0
.venv-External Baseline A\Scripts\python.exe -m pip install "External Baseline A-ai[proxy]==0.31.0"
ollama pull qwen2.5:1.5b
python -m benchmarks.compression_frontier run `
--External Baseline A-python .venv-External Baseline A\Scripts\python.exe `
--trials 60 --distractors 15 --runs 2 --warmups 1 `
--ollama-model qwen2.5:1.5b --answer-trials 8 `
--output benchmarks/results/compression_frontier.json `
--markdown benchmarks/results/compression_frontier.md `
--svg docs/assets/compression_frontier.svg
python -m benchmarks.compression_frontier verify `
benchmarks/results/compression_frontier.json
SQuAD v2 must already be cached; the runner refuses an implicit dataset download. Ollama is used only for the optional local answer guard.
This benchmark does not establish superiority across every task, compressor, provider, model, or production workload. SQuAD is extractive, the tool output is structured JSON, the local judge sample is small, and no retrieval or post-compression recovery is invoked. The Entroly participant is a source candidate until 1.0.59 is published; the artifact must not be described as a released-package result before that release exists.