Most small-parameter LLMs trade reasoning ability for footprint; ZAYA1-8B flips that expectation by using a Mixture-of-Experts design plus a post-training reasoning phase so a model with relatively few active parameters can match much larger models on formal math and coding benchmarks. The release targets scenarios where test-time compute and latency matter but you still need strong stepwise reasoning.
AI Model2026
ZAYA1-8B
Mixture-of-Experts LLM tuned for mathematical and coding reasoning, with ~760M active / 8.4B total parameters and post-training for improved stepwise reasoning. Optimized for inference efficiency (vLLM/transformers forks) so it can run in computation-constrained or local deployments; Apache-2.0 licensed.
Introduction
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- Websitehuggingface.co
- AuthorsZyphra
- Published date2026/05/04
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