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Published June 11, 2026 | Version v3

GCF: A Token-Optimized Wire Format for Structured LLM Interactions

Authors/Creators

Description

GCF is a proven lossless, bidirectional text-based wire format for LLM interactions. 1,300+ evaluations across 10 models from Anthropic, OpenAI, and Google. 

Comprehension: 90.7% average accuracy (four models at 100%) where JSON averages 53.6% and TOON averages 68.5%. Generation: 5/5 validity on every frontier model, zero training. TOON's official decoder rejects LLM-generated output on 7 of 9 models. 

Token efficiency: 79% fewer input tokens than JSON, wins all 6 datasets on TOON's own benchmark. Session deduplication (92.7% by 5th call) and delta encoding (81.2%) compound savings.

Six implementations (Go, TypeScript, Python, Rust, Swift, Kotlin), all at v1.0.0+ with CLIs. Bidirectional MCP proxy with session dedup, delta encoding, HTTP backend/frontend. 200M+ lossless round-trips verified. JSON Schema validation works on decoded output unchanged.

Files

gcf-whitepaper.pdf

Files (1.5 MB)

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md5:3060586dc21c75d4364785d1ff6ff92e
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Additional details

Software

Repository URL
https://github.com/blackwell-systems/gcf
Development Status
Active