Aplomb 1
Aplomb 1 by EmpirioLabs AI is a decision model: it answers typed questions with a probability for each allowed answer instead of generating text. It scores 43.8 on the Jev Decision Index (rank 70).
Pricing
No hosted price is listed. The weights are open: the cost is your own compute.
Specifications
- Provider
- EmpirioLabs AI
- Parameters
- 5B
- Released
- Sep 2026
- Open weights
- Yes
- Question types
- Choice (one of N options), Score (ordered rubric), Yes / no
- Mechanism
- Decoder LM with a decision readout
- Backbone
- Qwen/Qwen3.5-4B
- Jev-compatible request
- Yes
- Runs on CPU
- No
- License
- empiriolabs-model-license-1.0
- Hugging Face
- empiriolabsai/aplomb-1
Benchmarks
- Jev Decision IndexECE 0.075
- 43.8
- Jev Decision Index — VisionECE 0.049
- 57.3
Jev Decision Index: public 43.5, ECE 0.075, Brier 0.450. Lower ECE means its probabilities can be taken at face value.
Self-reported by the publisher
The model's own claims, often on its own sets or a self-run copy of a public suite. Not independently verified and never ranked alongside measured results.
- Typed Decisions (agreement with teacher)Self-reportedTyped Decisions test accuracy (fitted/fine-tuned on train), HF eval-results submission (unverified)
- 0.737
- Jev Decision Index public suite (self-run)Self-reportedDecision Index public balanced skill, edition 0.3 kit (release-v3), self-run
- 43.5
Speed & latency
Compare Aplomb 1 with…
FAQ
How much does Aplomb 1 cost?
Aplomb 1 has no hosted price listed; its weights are open, so the cost is the compute you run it on.
What questions can Aplomb 1 answer?
Aplomb 1 answers choice (one of n options), score (ordered rubric), yes / no questions, returning a probability for each allowed answer.
Is Aplomb 1 well calibrated?
On the Jev Decision Index its expected calibration error (ECE) is 0.075; below about 0.05, a stated 80% confidence is right roughly 80% of the time.
Is Aplomb 1 open weight, and can it run on a CPU?
Yes, Aplomb 1 has open weights. It needs a GPU to run at useful speed.
Data as of 2026-10-14. Source: Metatext decision-model catalogue, 2026-10-14 (Jev Decision Index, Benchmark Heaven JevBench, Hugging Face). Pricing is per 1M tokens (USD); confirm with the provider before production use.