BLAKE3
Lightning-fast BLAKE3 cryptographic hash - 3x faster than BLAKE2 with parallel processing
Short explanation
BLAKE3 is a modern cryptographic hash designed for high performance, parallelism, and flexible output. It is commonly used when speed matters but a cryptographic hash is still required.
Example input
video-segment-00042Typical use
Use BLAKE3 to hash large files, chunks, or streams quickly while keeping cryptographic-strength digest properties.
When to use it
- High-throughput file hashing, chunking, and content-addressed storage.
- Applications that benefit from parallel hashing on modern CPUs.
- Modern systems where BLAKE3 support is available on both producer and consumer sides.
When not to use it
- Protocols or audits that require SHA-2 or SHA-3 specifically.
- Password storage; use Argon2id or another password hashing algorithm.
- Legacy integrations that cannot consume BLAKE3 digests.
FAQ
Is BLAKE3 cryptographically secure?
BLAKE3 is designed as a cryptographic hash and is considered a strong modern choice, though some standards and compliance programs still require SHA-2 or SHA-3.
Why is BLAKE3 fast?
BLAKE3 uses a tree structure and is built for parallelism, so it can use modern CPU resources efficiently.
Can BLAKE3 output different lengths?
Yes. BLAKE3 supports extendable output, though many tools use a 256-bit output by default.
Lightning-fast BLAKE3 cryptographic hash - 3x faster than BLAKE2 with parallel processing
cSHAKE128
cSHAKE128 customizable XOF - domain-separated SHAKE128 for protocol customization and security
cSHAKE256
cSHAKE256 customizable XOF - enhanced domain separation for cryptographic protocol design
TurboSHAKE128
TurboSHAKE128 with domain separation - optimized XOF for high-performance cryptographic applications
TurboSHAKE256
TurboSHAKE256 with domain separation - high-security XOF for advanced cryptographic protocols
TupleHash
TupleHash for ordered sequences - secure hashing of structured data with tuple preservation
ParallelHash
ParallelHash for large data - high-performance parallel processing of massive datasets