OPEN
REAX 1.3
REAX 1.3 averages probabilities from two model parts on one GPU. Its open weights and MIT engine include results from its own Decision Index runs.
By REAX · Released 3 Nov 2026
REAX 1.3 runs two model parts on one GPU and averages their per-option probabilities 50/50. One blends a Bittensor subnet 92 miner fine-tune with KnowLine; the other blends a miner fine-tune from Mammoth-1's lineage with Decision 1.0's d3-ultra. Its interface accepts Jev-style requests. The hosted service at decisionmodels.io and the Hugging Face account decisionmodels belong to a separate business unrelated to decisionmodels.ai.
Facts
- Licence
- Apache-2.0 for the blended work, subject to preserved upstream licences and notices; REAX Engine is MIT
- Weights
- About 115 GB in FP8; reference hardware is one RTX PRO 6000 Blackwell 96 GB
- Inputs
- Text; noul, choice and score questions
- Access
- Open Hugging Face weights and REAX Engine reax13 mode
- Local input cap
- 32,000 proxy tokens, calculated from compact request JSON characters divided by four, rounded down; larger requests are refused.
Claims and sources
- REAX reports 73.71 on all 140,178 scoreable public Decision Index 0.3 requests. Counting the one request above the released engine's input cap as refused gives 73.70. These are internal measurements, not official leaderboard scores. vendor reportedsource
- On 3,478 public items answered by all eight models, REAX reports 69.5 against 68.8 for d3-ultra, within noise, and 67.4 for KnowLine. The second draw was added after a partial result was known. The public subset cannot establish an official Full-score ranking. vendor reportedsource
- On a uniform 1,000-call sample, REAX measures 207 ms median and 655 ms mean latency, one request at a time on one RTX PRO 6000. Long multi-question requests can take minutes. vendor reportedsource
Links
Source: Weights, results and upstream notices → Source: REAX Engine → Source: Announcement →
Related projects
No related projects are listed in the registry.