Benchmark of Rust PRNG crates

Simple performance benchmark of pseudorandom generation Rust crates for non-cryptographic purposes such as games.

The goal is not to compare algorithms, but implementations that can be used immediately by a Rust developer.

Inclusion criteria:

• Seedable. Needed for reproducibility.
• Simple to use, either thanks to an obvious API or examples in documentation.
• Works on common targets.
• Usable for generating bytes or groups of bytes.
• Builds on my system.

Warning: If your need has anything to do with security, i.e. generating values seeded by or interacting with potentially untrusted data or that should be secret or not leak information about the seed or correlation between multiple outputs, then you should instead use a CSPRNG.

Results

RUSTFLAGS='-C target-cpu=native' cargo run --release

rustc 1.95.0-nightly (57d2fb136 2026-02-01)

Results on AMD Ryzen 7 5700X: (with AVX2)

Time (s)        PRNG
0.06720725      simd_rand::specific::avx2::xoshiro256plusplus::Xoshiro256PlusPlusX4
0.06825219      simd_rand::portable::xoshiro256plusx4::Xoshiro256PlusX4
0.06890218      simd_rand::specific::avx2::xoshiro256plus::Xoshiro256PlusX4
0.069135666     simd_rand::portable::xoshiro256plusplusx4::Xoshiro256PlusPlusX4
0.07073431      simd_rand::portable::xoshiro256plusx8::Xoshiro256PlusX8
0.07283282      simd_rand::portable::xoshiro256plusplusx8::Xoshiro256PlusPlusX8
0.07305191      frand::Rand
0.076635174     fast_rands::RomuDuoJrRand
0.07750931      rand_xoshiro::xoshiro256plus::Xoshiro256Plus
0.0798837       wyhash::v1::traits::WyRng
0.08170648      fast_rands::RomuTrioRand
0.082019165     romu::Rng
0.08613385      simd_rand::specific::avx2::shishua::Shishua<32768>
0.08767373      tinyrand::wyrand::Wyrand
0.08789389      wyhash::final3::traits::WyRng
0.087896034     fastrand::Rng
0.08798213      wyrand::final_v4_2::wyrand::WyRand
0.089724645     rand_xoshiro::xoshiro256starstar::Xoshiro256StarStar
0.090424806     rand_xoshiro::xoroshiro128plus::Xoroshiro128Plus
0.09778529      tiny_prng::pcg::PcgXslRr6432Mcg
0.098746814     rand_xoshiro::xoroshiro128plusplus::Xoroshiro128PlusPlus
0.10192768      rand_xoshiro::xoroshiro128starstar::Xoroshiro128StarStar
0.10222766      fast_rands::Xoshiro256PlusPlusRand
0.1025012       rand_xoshiro::xoshiro256plusplus::Xoshiro256PlusPlus
0.10895407      rand::rngs::small::SmallRng
0.109856725     rand_xoshiro::xoshiro512plus::Xoshiro512Plus
0.1161916       tinyrand::xorshift::Xorshift
0.11952907      shishua::core::ShiShuAState
0.1273132       tiny_prng::pcg::PcgXslRrMcg
0.1313371       tiny_prng::xorshift::Xorshift1024star
0.13799635      tiny_prng::xorshift::Xorshift128
0.1382492       rand_xoshiro::xoshiro512plusplus::Xoshiro512PlusPlus
0.13890779      rand_xoshiro::xoshiro512starstar::Xoshiro512StarStar
0.14007749      rand_xoshiro::splitmix64::SplitMix64
0.14576794      rand_xoshiro::xoshiro128plus::Xoshiro128Plus
0.15051891      fast_rands::Sfc64Rand
0.1522026       tiny_prng::pcg::PcgXslRr
0.15726987      tinyrand::splitmix::SplitMix
0.15869391      prng_mt::mt19937::MT19937_64
0.15959476      rand_xoshiro::xoshiro128starstar::Xoshiro128StarStar
0.1698655       bsd4random::BSD
0.17368329      tiny_prng::xorshift::Xorshift64
0.17383604      rand_xoshiro::xoroshiro64star::Xoroshiro64Star
0.17391294      fast_rands::XorShift64Rand
0.1766414       fast_rands::Lehmer64Rand
0.17737824      tiny_prng::xorshift::Xorshift64star
0.18385774      mcg59::MCG59
0.18856412      rand_xoshiro::xoshiro128plusplus::Xoshiro128PlusPlus
0.20034873      tiny_prng::mt64::Mt19937
0.21738203      rand_xoshiro::xoroshiro64starstar::Xoroshiro64StarStar
0.21857128      aes_prng::AesRng
0.23149101      tiny_prng::pcg::PcgXshRs6432
0.23159662      tiny_prng::pcg::PcgXshRr6432
0.28765705      rand::rngs::std::StdRng
0.29028276      prng_mt::mt19937::MT19937
0.3162913       quad_rand::RandGenerator
0.34691545      tiny_prng::xorshift::Xorshift32
0.34718052      nanorand::rand::wyrand::WyRand
0.3953146       tiny_prng::mt::Mt19937
0.40042716      nanorand::rand::pcg64::Pcg64
0.9632352       nanorand::rand::chacha::ChaCha<8>
1.772863        shishua::rand::ShiShuARng
3.5408454       acorn_prng::Acorn
3.706891        simplerand::Random

Results on Intel Core i5-7300HQ: (with AVX2)

Time (s)	PRNG
0.08816869	simd_rand::specific::avx2::xoshiro256plusplus::Xoshiro256PlusPlusX4
0.08920241	simd_rand::portable::xoshiro256plusplusx4::Xoshiro256PlusPlusX4
0.0916341	simd_rand::portable::xoshiro256plusx4::Xoshiro256PlusX4
0.091638505	frand::Rand
0.09203979	simd_rand::portable::xoshiro256plusx8::Xoshiro256PlusX8
0.09215377	simd_rand::specific::avx2::xoshiro256plus::Xoshiro256PlusX4
0.10456483	fast_rands::RomuDuoJrRand
0.10739412	romu::Rng
0.10897199	fast_rands::RomuTrioRand
0.11360018	simd_rand::specific::avx2::shishua::Shishua<32768>
0.12551166	rand_xoshiro::xoshiro256plus::Xoshiro256Plus
0.12791388	simd_rand::portable::xoshiro256plusplusx8::Xoshiro256PlusPlusX8
0.13942851	rand_xoshiro::xoshiro256starstar::Xoshiro256StarStar
0.14631735	rand_xoshiro::xoroshiro128plus::Xoroshiro128Plus
0.14701757	fast_rands::Xoshiro256PlusPlusRand
0.14716452	rand_xoshiro::xoshiro256plusplus::Xoshiro256PlusPlus
0.16382654	tinyrand::wyrand::Wyrand
0.16435602	shishua::core::ShiShuAState
0.16689982	wyrand::final_v4_2::wyrand::WyRand
0.16744553	fastrand::Rng
0.16864042	rand_xoshiro::xoroshiro128starstar::Xoroshiro128StarStar
0.16963984	wyhash::final3::traits::WyRng
0.17015934	wyhash::v1::traits::WyRng
0.17045826	rand::rngs::small::SmallRng
0.1716554	rand_xoshiro::xoroshiro128plusplus::Xoroshiro128PlusPlus
0.17414004	tinyrand::xorshift::Xorshift
0.17646453	fast_rands::Sfc64Rand
0.18034014	rand_xoshiro::splitmix64::SplitMix64
0.18191795	tiny_prng::xorshift::Xorshift1024star
0.19055116	tiny_prng::xorshift::Xorshift128
0.1933505	rand_xoshiro::xoshiro512plus::Xoshiro512Plus
0.2013804	tiny_prng::pcg::PcgXslRrMcg
0.2033752	rand_xoshiro::xoshiro512starstar::Xoshiro512StarStar
0.2053617	mcg59::MCG59
0.20707493	fast_rands::Lehmer64Rand
0.21336877	rand_xoshiro::xoshiro512plusplus::Xoshiro512PlusPlus
0.22039062	tinyrand::splitmix::SplitMix
0.23350179	tiny_prng::pcg::PcgXslRr
0.23514548	bsd4random::BSD
0.23781174	fast_rands::XorShift64Rand
0.23798868	tiny_prng::xorshift::Xorshift64
0.23917288	tiny_prng::xorshift::Xorshift64star
0.24470972	rand_xoshiro::xoshiro128plus::Xoshiro128Plus
0.2509169	tiny_prng::pcg::PcgXslRr6432Mcg
0.29076266	rand_xoshiro::xoshiro128starstar::Xoshiro128StarStar
0.3070184	rand_xoshiro::xoshiro128plusplus::Xoshiro128PlusPlus
0.31972992	aes_prng::AesRng
0.32094362	tiny_prng::pcg::PcgXshRs6432
0.3234704	prng_mt::mt19937::MT19937_64
0.33205837	tiny_prng::pcg::PcgXshRr6432
0.3321641	rand_xoshiro::xoroshiro64star::Xoroshiro64Star
0.37840256	rand_xoshiro::xoroshiro64starstar::Xoroshiro64StarStar
0.42188576	quad_rand::RandGenerator
0.45290765	rand::rngs::std::StdRng
0.46695596	tiny_prng::xorshift::Xorshift32
0.47651544	prng_mt::mt19937::MT19937
0.47986245	nanorand::rand::wyrand::WyRand
0.5589406	tiny_prng::mt64::Mt19937
0.6100908	nanorand::rand::pcg64::Pcg64
1.146011	nanorand::rand::chacha::ChaCha<8>
1.442915	tiny_prng::mt::Mt19937
1.7194357	shishua::rand::ShiShuARng
3.682478	acorn_prng::Acorn
15.616315	simplerand::Random

FRand is the fastest, however it has no particular mathematical justification beyond the fact its parameters were found empirically to minimize bias.

simd_rand provides the fastest implementations of common PRNGs. The best on my computer (without AVX512) was a portable one, probably thanks to compiler autovectorization. Sadly this crate is not published on crates.io, only on GitHub.

fast_rands implements RomuDuoJr, the fastest after simd_rand. It is part of the Romu family which has been studied. It provides good quality up to at least 2^48 bytes. However this crate has too many dependencies that should not be necessary if you only want a PRNG, so copying the wanted functions can be an option.

Surprisingly, the AES PRNG is quite fast, probably due to the AES instruction set.

Also to my surprise, Shishua was slower than RomuTrio, contrarily to the author's claim. Maybe that's the implementation's fault or my lack of AVX512, I should investigate. The streaming overhead can be significant, as we see with ShiShuARng which is very slow compared to the bare ShiShuAState. simd_rand's implementation is quite faster.