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