Decido 1 family decision model

Decido 1 includes direct-readout, small distilled and reasoning variants. Its cards report CPU timing and disclose supervised benchmark training overlap.

By decido-ai · Weights upload: 7 Nov 2026

Six English document-decision packages share the decido API. Decido-1, Max and Think use Gemma-4-26B-A4B; Fast uses Qwen3-1.7B, Ultra Qwen3-0.6B and XL DeepSeek-V4-Flash. Max distils a three-model research mixture into one checkpoint and generates up to 1,024 reasoning tokens before reading option probabilities. The Max package’s GPU serving path is still being validated.

Quick answers

Facts

Variants

Decido-1, Fast 1.7B, Ultra 0.6B, Think and Max 26B-A4B, XL

Inputs

English text or JSON; choice, noul and score

Licence

Apache-2.0 for the five Gemma/Qwen packages; MIT for the XL adapter, with separate base-model terms

Runtime

decido-ai package; GGUF and bf16 packages vary by variant

Speed

Maker reports M4 Pro CPU medians of 4.1 s for Decido-1, 0.64 s Fast and 0.41 s Ultra for a roughly 1k-token state and five questions. Think takes 19 s per question. Max reports 10.1 s p50 for five parallel questions on an A100 80 GB, or about 11 s per question on M4 Pro Metal and 28 s on CPU; no full CPU/Metal accuracy run is supplied.

Claims and sources

• The maker reports six-group means of 85.38 for Decido-1 on CPU, 73.01 Fast and 62.16 Ultra. The OpenJev group uses CUDA with the same GGUF, checked against a smaller CPU sample. Training includes public train splits from scored datasets; Jev's published reference run uses a different harness and 19 OpenJev tasks against Decido's 18. vendor reportedsource
• Max reports a six-group mean of 89.23 (95% interval 88.25 to 90.15), against a published Jev 1.13 reference at 83.85. Training uses train splits from scored datasets; Jev is zero-shot and was not rerun in the same harness. Decido uses 18 OpenJev tasks against the reference’s 19. The in-domain comparison is not a general model ranking. vendor reportedsource
• Repeating 50 GPU requests changes Max’s top answer 8% of the time. The card reports identical repeats on CPU and Metal, with answer agreement against GPU on 15 CPU and 101 Metal questions. Those small checks are not complete local accuracy evaluations. vendor reportedsource
• Think’s reported 88.71 six-group mean is rescored from its outputs inside the Pro mixture. For 157 Kev questions the router never sent to Think, Decido-1 answers are used. The reasoning cap is hit on 46% of OpenJev questions. A 60-question CPU sample agrees with recorded GPU choices 98.3% of the time; no full CPU accuracy run is supplied. vendor reportedsource

Links

Source: Decido-1 card and weights → Source: Fast card and weights → Source: Ultra card and weights → Source: Think card and weights → Source: Max card and weights → Source: XL card and weights →

Related projects

No related projects are listed in the registry.

All projects · Back to the model registry