Models & Weights

ZAYA1

The existence proof that open models don't need NVIDIA

Open ✓Model

What it is

Zyphra's reasoning MoE — 8.4B total parameters, 760M active — pretrained end-to-end on AMD Instinct MI300X GPUs, the first credible frontier-recipe run on an all-AMD stack. Ships as base, reasoning, and vision-language variants, all Apache-2.0, with a full technical report.

Why it's interesting

Punches far above its 760M active parameters on math and reasoning, and the hardware story matters as much as the scores: every proven alternative to the CUDA monoculture makes open AI harder to choke off.

Use cases

  • Efficient reasoning on modest GPUs
  • Studying MoE training outside the NVIDIA stack via the tech report
  • Fine-tuning a small reasoner you can deploy cheaply

Who it's for

Researchers, efficiency-minded ML engineers, AMD-curious infrastructure teams

Setup

Easy. Inference via transformers or vLLM; the 8.4B model fits comfortably on a 24GB GPU, with the tiny active footprint keeping it fast

Limitations & cautions

The small activation budget shows outside math and reasoning, coverage is English-centric, and the training data itself is not released — this is open weights and recipe, not OLMo-grade full provenance.

Editorial takeaway

The scores are good; the supply chain is the headline. Open AI got measurably harder to strangle the day this training run finished.

Related & alternatives