Fastino's open-weight decision model. A DeBERTa-v3-large encoder that scores label sets supplied at runtime, answers single-label, multi-label, yes/no and ordinal questions in one pass, and extracts spans and relations.
Together AI's Jev-style classifier. A LoRA fine-tune of Qwen3.5-4B that reads a state, a question and 2 to 24 options and returns one option letter. Served on Together's platform; recipe published.
Decides
choice, score, noul, classify, extract, route
choice, classify, route
Architecture
gliner2
tev
Fine-tuned from
fastino/gliner2-large-v1
qwen/qwen3.5-4b
License
apache-2.0
Unspecified — weights licence being finalised
Availability
Open weights + hosted API
Open weights + hosted API
Hosted by
Fastino
Together AI
Input price
—
$0.042/MTok
Decision accuracy
60.2%
88.0%
Calibration error
—
—
Valid action rate
—
—
Median latency
38.3 ms
—
p95 latency
—
—
Evaluation suite
Fastino fast-decisions suite (17 datasets)
Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
Questions
What is the difference between gliner2-5-decide and tev1?
gliner2-5-decide is from Fastino Labs and tev1 from Together AI. Both have open weights and a hosted API. Both answer choice, classify and route questions. Only gliner2-5-decide answers score, noul and extract. gliner2-5-decide is the smaller model, at 340M parameters to 4.0B. gliner2-5-decide is licensed apache-2.0; tev1, other.
Which is more accurate, gliner2-5-decide or tev1?
They report on different suites — gliner2-5-decide 60.2% on Fastino fast-decisions suite (17 datasets), tev1 88.0% on Together development set (reused, not held out) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, gliner2-5-decide or tev1?
gliner2-5-decide: Hosted, price not published, or free to self-host. tev1: $0.042 / $0 per 1M, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run gliner2-5-decide or tev1 locally?
Yes, both: systemone pull fastino-labs/gliner2-5-decide and systemone pull together-ai/tev1 download the weights.
