YASAKANI Claims 1,220 Tokens/Second on RTX 5090
YASAKANI claims 1,220 tokens/second running Qwen3.8-27B on a single stock RTX 5090, reportedly up to 2.5× faster than competing local inference engines. The result is self-reported and lacks publicly documented quantization and methodology details.
YASAKANI’s headline number is striking, but it is best treated as an intriguing performance claim until independent developers can reproduce it.
- –The reported speed is far above documented RTX 5090 results from engines such as MegaCapybara and Infernix.
- –Missing details on quantization, context length, draft model, and measurement procedure make direct comparisons difficult.
- –If reproducible, the engine could make high-end local coding agents feel nearly instantaneous on consumer hardware.
- –The result highlights how specialized kernels and speculative decoding can matter as much as raw GPU performance.
- –Developers should wait for source code, downloadable builds, and quality-throughput comparisons before treating 1,220 tokens/second as a production benchmark.
DISCOVERED
2h ago
2026-11-04
PUBLISHED
2h ago
2026-11-04
RELEVANCE
AUTHOR
crazyMLguy