decisio v0.8.0 on gemma-4-12B-it (frozen, one forward pass, self-hosted)
Data: JevBench v1.6.1, published 2026-10-06
Capability 70.7 · rank #15 of 92 on the open-weights board
Last measured: 2026-10-06 · measurement release: v1.6.1
Apache-2.0 software; Gemma model terms
intelligence
52.3
calibration
89.2
speed
87.0
cost
59.3
Composite (secondary)
68.2 · Composite rank #10
Cost and measurement conditions
$0.023 per 1,000 decisions (estimated)
ESTIMATE (base-model reference; self-hosted open weights, no public tariff): the exact base google/gemma-4-12B-it is in the frozen pricing module's UNLISTED_BASE_MODELS set, so no exact base-model rate and no floor exist. The reference is the one the rows PUBLISHED on this same base use - cygnet, jev-omni and winnow-12b - OpenRouter google/gemma-3-12b-it, the nearest publicly hosted 12B Gemma sibling, at its FULL catalog pair USD 0.05 per 1M input and USD 0.15 per 1M output. PREREG-R54-AMENDMENT-1 uses the full pair rather than run 53's output=0, so a row that emits tokens pays for them; where a row generates nothing the output term is zero anyway. x this row's own measured input/output tokens, the deck31b method. Estimated, not charged
Measured p50 latency: 0.102 s (on-GPU, no network, loopback; not directly comparable with API latency, which we time end to end from our measuring host, network included)
Ranking and cap use: 0.35 s (est. incl. network (2x + 150 ms))
Self-hosted model: measured p50 0.102 s on-GPU, no network (timed on our GPU over loopback). Not directly comparable with API latency, which we time end to end from our measuring host, network included. The ranking and latency cap use the same estimate for every self-hosted row: 2 × measured + 150 ms = 0.35 s. Model authors can ask us to time a hosted endpoint instead (on request).
x2 + 0.15 s (assumption, not measured)
measured 2026-10-06 on the live v1.6.0/v1.6.1 pool. github.com/aminry/decisio tag v0.8.0 (5b42101a191d222062a795194b0aedb5003bf6ea, verified against the GitHub refs API), installed with their own `uv sync --extra serve --frozen` so their lockfile fixes every version, and served with their own `python -m decisio.serve.vllm_engine --base gemma-4-12b`. --base carries google/gemma-4-12B-it@707f0a3b (bf16, 22.8 GiB) and that profile's measured settings - temperature 3.592 for every question type, a system turn, the chat template's own answer position, every single-token form of each letter summed. Frozen base: no fine-tuning, no adapter, no task registered. One RTX 6000 Ada 48 GB (Lium, Toronto). Latency axis uses the standard self-hosted x2 + 0.15 s adjustment. add-requests run 54, GitHub #169