H33 vs Lattigo: Production FHE Compared
Why a Rust production pipeline with integrated attestation outperforms a Go FHE library
Lattigo is an open-source Go library for lattice-based homomorphic encryption, developed by researchers at EPFL. It implements BFV, BGV, and CKKS schemes with a clean Go API, making it one of the most accessible FHE libraries available. For researchers who want to experiment with FHE in a garbage-collected language, Lattigo is a reasonable starting point. But when the question shifts from experimentation to production deployment, the answer reveals a fundamental gap.
H33 is not a library. It is a production pipeline combining FHE with STARK zero-knowledge proofs and three-family post-quantum signatures in a single binary. When you call H33, data is encrypted, computation verified, and results signed with ML-DSA-65, FALCON-512, and SLH-DSA-SHA2-128f, then distilled into a 74-byte H33-74 attestation. Lattigo gives you the encryption step. Everything else is your problem.
Language: Rust vs Go
Lattigo is written in Go. Go provides garbage collection, goroutine-based concurrency, and a simple type system. These make development faster but introduce suboptimal performance for FHE. Garbage collection pauses cause unpredictable latency spikes. The Go memory allocator is optimized for general workloads, not FHE's pattern of large polynomial buffers allocated and freed in tight loops.
H33 is written in Rust with zero-cost abstractions, compile-time memory safety without GC, and direct memory control. The system allocator on Graviton4 is optimized for tight FHE loops across 192 concurrent workers. No GC pauses, no unexpected allocations, deterministic performance.
FHE Scheme Coverage
Lattigo implements BFV, BGV, and CKKS but not TFHE. H33 implements BFV, CKKS, and TFHE. TFHE enables gate-by-gate encrypted boolean computation impossible with BFV or CKKS. For encrypted comparisons, string matching, or control flow, TFHE is essential. Lattigo users needing TFHE must integrate a separate library in a different language.
H33's FHE-IQ routing layer automatically selects the optimal scheme per sub-computation, manages parameter compatibility, and handles scheme conversions. Lattigo provides individual implementations without routing or bridging.
Performance: Pipeline vs Library
Comparing raw FHE speed is misleading. Lattigo benchmarks measure isolated operations. H33 benchmarks measure the complete pipeline including FHE, ZKP, and PQ signing.
H33 on AWS Graviton4: 2,293,766 authentications per second at 38 microseconds each. BFV with 4,096 SIMD slots, STARK verification, three-family signing included. The FHE stage takes 943 microseconds per 32-user batch (70% of pipeline).
Lattigo has no equivalent benchmark because it is not a pipeline. Achieving comparable functionality requires integrating ZKP, PQ signatures, and caching -- each boundary adding serialization overhead invisible in isolated benchmarks but dominant in production.
Post-Quantum Security
Lattigo's RLWE-based FHE is quantum-resistant for encryption. But without signing or attestation, a Lattigo-based system with ECDSA signatures has quantum-resistant encryption and quantum-vulnerable attestation. H33 provides three independent PQ families: ML-DSA-65 (MLWE), FALCON-512 (NTRU), SLH-DSA-SHA2-128f (hash). The H33-74 substrate distills this to 74 bytes -- not compression but distillation preserving three-family guarantees.
Deployment
Lattigo deployment requires building a Go application, implementing your API layer, managing keys, handling serialization, building monitoring. No Docker images, no ARM optimization, no production benchmarks.
H33 deploys as a single Rust binary with REST API, Docker images for x86 and ARM64, built-in metrics. Hours versus months of engineering.
The Integration Tax
Using Lattigo for production means integrating ZKP, PQ signatures, caching, key management, API, serialization, monitoring, and auditing -- all separately. H33 provides a single audited pipeline where FHE, ZKP, and PQ signing are co-designed. The integration surface where bugs hide is eliminated.
When Each Is Right
Lattigo is right for research, prototyping, and Go codebases needing FHE as a component. H33 is right for production deployment with verification, attestation, and post-quantum security. The gap is engineering years, not weeks.
Contact support@h33.ai for a technical comparison tailored to your workload.