H33 vs Zama Concrete: FHE Compilers Compared
Why Rust-native production FHE with attestation outperforms a Python FHE compiler
Zama Concrete represents an important thesis: FHE complexity can be hidden behind a Python compiler. Write a function, annotate inputs as encrypted, and Concrete generates the circuit. For accessibility, it is a genuine contribution. But accessibility and production readiness are different properties.
H33 is a Rust-native production pipeline with BFV, CKKS, and TFHE, STARK proofs, and three-family PQ signatures. It processes 2,293,766 authentications per second at 38 microseconds each on Graviton4. Single binary, REST API, zero serialization between stages.
Python Overhead
Concrete compiles to Rust/C for FHE operations -- the hot loop is not Python. But orchestration is: parameter selection, circuit optimization, key management, encoding, decoding. For production throughput, the GIL, memory management, and Python-to-native serialization become significant. H33 runs everything in Rust. No interpreter, no GIL, no serialization between layers. 192 workers run in parallel without contention.
Scheme Coverage
Concrete is TFHE-only. BFV is dramatically faster for integer arithmetic (batch polynomials vs individual bits). CKKS provides native floating-point for ML inference. H33's FHE-IQ routes each sub-computation to its optimal scheme. Concrete users needing BFV or CKKS lose compilation convenience.
Attestation
Concrete provides computation without verification, signing, or attestation. For regulated industries, results without provenance are useless. H33 includes STARK proofs, three-family PQ signatures (ML-DSA-65, FALCON-512, SLH-DSA-SHA2-128f), and 74-byte H33-74 distillation -- integral to the pipeline, not an add-on.
Production Readiness
Concrete targets development: Python interface, Jupyter support, automatic parameters. H33 targets production: Rust binary, REST API, Docker, ARM64 optimization, built-in metrics. Concrete needs a Python environment and custom API wrappers. H33 needs a binary and environment variables.
Performance
H33: 2,293,766 auth/sec sustained, 38 microseconds each, BFV with 4,096 SIMD slots plus STARK plus three-family signing. FHE stage: 943 microseconds per 32-user batch. TFHE fundamentally operates at lower throughput than BFV for workloads BFV handles.
When Each Is Right
Concrete excels for data scientists exploring FHE, rapid prototyping in Jupyter, and TFHE-specific workloads. H33 is for production throughput, multi-scheme FHE, integrated attestation, and post-quantum security. The gap between accessible and deployable is the gap between research and production.
Contact support@h33.ai to evaluate which fits your requirements.
How This Fits: Mechanisms This Page Uses
This comparison is owned by the FHE Platform, which computes on encrypted data. Where H33's pipeline is described, it uses neighboring capabilities rather than being them: it uses the ZK Platform for STARK proofs of correct computation, it uses PQ-Verified conformance for its three-family post-quantum signatures, and it uses H33-74 to produce the portable attestation. The FHE Platform does not own proving or attestation; it references those owners.
Where To Go Next (Boundary)
If your question is about proving-without-revealing rather than computing on ciphertext, see the ZK Platform. If it is about post-quantum conformance, see PQ-Verified. For portable evidence, see H33-74.
Frequently Asked Questions
What is Zama Concrete?
A Python FHE compiler converting functions to encrypted TFHE circuits automatically.
How does H33 differ?
H33 is Rust-native with BFV+CKKS+TFHE, STARK proofs, and three-family PQ signatures. Concrete is Python TFHE-only.
Python overhead?
Concrete compiles FHE to Rust/C but orchestration is Python. H33 runs everything in Rust with zero interpreter overhead.
PQ signatures in Concrete?
No. Concrete provides FHE only.
Which FHE schemes?
Concrete is TFHE-only. H33 supports BFV, CKKS, and TFHE with automatic routing.
See Also
- FHE Platform — computing on encrypted data
- ZK Platform — proving without revealing
- PQ-Verified — post-quantum conformance