Why it exists
Every LLM call ships a pile of context: RAG chunks, chat history, tool dumps, logs, JSON. Most of it is irrelevant to the current question — but the model still reads it, and you still pay for it.
SuperCompress v2 compresses context against the query. It keeps answer-critical lines in their original wording and drops the rest — on our coding-agent benchmark (B5), 64.1% mean context reduction with 24/24 evidence-retention passes.
Product
SuperCompress is a compression layer in front of inference:
- Takes a long context + the current query
- Segments and scores blocks by relevance to that query
- Keeps entities, errors, definitions, nearby dependencies
- Returns a smaller prompt + token stats
The query is never compressed — only the surrounding context.
Two paths
Two products
Docs: coding agents (first 5 minutes checklist) · API quickstart
Repo map
Private marketing, outreach, and model training stay out of this repo (see .gitignore + docs/REPO_LAYOUT.md).
Benchmarks & stats
We measure whether required evidence survives (containment), not downstream LLM completion.
Neural v2 launch (hosted ~400M) — B5 coding-agent suite
Aggregate mean cut across all 390 cases is ~3.6% — the engine often refuses to over-cut dense needle/QA slices. The 64.1% figure is the coding-agent suite where dumps are noisy.
Raw JSON: launch-benchmark.json · writeup: benchmarks
Legacy compiler (separate product)
CPU / millisecond-class local path. Older held-out compiler numbers (≈58–66% cut, 99.4% gold containment) live under Legacy/compiler on /benchmarks. Do not mix with Neural v2.
Try it
Coding agents (recommended)
npm install -g supercompress-proxy
npx supercompress setup
Links your account, detects agents, installs MCP. Docs: coding agents
Python / HTTP
pip install supercompress
export SUPERCOMPRESS_API_KEY=sc_live_YOUR_KEY
from supercompress.client import SuperCompress
sc = SuperCompress()
result = sc.compress(
context=long_context,
query="What failed and how do we fix it?",
)
print(f"{result.original_tokens} → {result.kept_tokens} tokens")
print(result.compressed_text)
curl -X POST https://www.supercompress.dev/api/v1/compress \
-H "X-API-Key: $SUPERCOMPRESS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"context":"...","query":"What failed?"}'
Or paste a dump into the Arena — no integration required.
How it compares
More: vs truncation · vs summarization · vs alternatives