ollaya-dev/sura-0.8b

Sura 0.8b

In Ollaya's registry as sura:0.8b. Ollaya's runtime matches upstream pplx_decider on all 696 parity questions (CPU and CUDA). On Ollaya Bench 2026.10 it scores 37.2 (typed-decisions 0.560, public benchmark macro accuracy 0.586): level with coba:1b, below decider:0.8b and kev:0.8b. sura-2b is the more accurate tag.

Sura 0.8b is a decision model by Ollaya. The smaller sura, aimed at the best accuracy under 1B parameters. Give it a state (a message, a support ticket, a JSON object, an agent's next tool call) and questions, and it answers every question in one forward pass with calibrated probabilities:

• noul: yes or no, as the probability of yes;
• choice: one of up to 255 options, each described in plain words;
• score: a level on a scale of described levels.

Ollaya's model families

Family	Network	Built for
coba	encoder (Ettin), 68M to 1B	speed: CPUs, and the browser at 35 to 147 MB
sura	decoder (Qwen3.5)	accuracy

Model	Base	Status
sura-0.8b	Qwen/Qwen3.5-0.8B-Base	sura:0.8b; Ollaya Bench 37.2
sura-2b	Qwen/Qwen3.5-2B-Base	sura:2b and sura:latest; Ollaya Bench 40.9

How it is built

• Network: the joint inline-readout protocol of Perplexity's pplx-decider (version 3). Every question of a request shares one sequence with the state; each question is followed by its options and a marker, and a 255-way linear readout scores the options at that marker. The full-attention layers see the whole sequence; the Gated DeltaNet layers stay causal.
• Teacher: perplexity-ai/pplx-decider-flash-v1.2 (Qwen3.5-4B, Apache-2.0). The student shares its tokenizer and prompt, so it learns the teacher's full distribution over the options, not only its answers.
• Data: the mixture of coba's zero-shot models, about 340,000 states with gold and teacher labels. It holds none of the datasets of the benchmarks Ollaya reports, so the results are zero-shot.
• License: Apache-2.0, like the base model and the teacher.

Run it

With Ollaya (Linux, macOS, Windows; CPU, CUDA, Metal):

curl -fsSL https://ollaya.dev/install.sh | sh
ollaya run sura:0.8b --ask "Is the customer asking for a refund?" < ticket.txt

Files

• model.safetensors (BF16 backbone) and readout.safetensors (the 255-code readout).
• The teacher's processor files (tokenizer, chat template, joint_config.json), so upstream's pplx_decider loads this directory as a pplx-decider checkpoint.
• source/: Perplexity's pplx_decider package from pplx-decider-flash-v1.2, unchanged (Apache-2.0, see NOTICE).