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JevBench by Benchmark Heaven · v1.4.2.2 · individual system

GLiNER2 (Fastino, gliner2.5-base)

Zero-shot classifier · by Fastino

JevBench v1.4.2.2 score

11.8

Rank #75 of 91 ranked systems.

51.5 points behind Jev 1.13.0's 63.3.

Where it sits among the 91 ranked systems. The marked tick is Jev 1.13.0 (63.3).

Published axes

intelligence
27.4
calibration
25.2
speed
71.8
cost
83.1

Against Jev 1.13.0

Four radars compare this fixed pair across the score axes, accuracy per tier, and accuracy by family on the hard tier and sealed set. Further out is better on every spoke.

  • A: GLiNER2 — Zero-shot classifier · Score 11.8 (#75)
  • B: Jev 1.13.0 — Jev (TypeSafe, closed) · Score 63.3 (#4)

The four score axes

Radar: the four score axes, two systemsThe four score axes, GLiNER2 vs Jev 1.13.0. Intelligence: 27.4 vs 53.1; Calibration: 25.2 vs 76.3; Speed: 71.8 vs 83.3; Cost: 83.1 vs 52.0.50100Intelligence27.4 · 53.1Calibration25.2 · 76.3Speed71.8 · 83.3Cost83.1 · 52.0
0–100, the values in the table. A label-only system has no calibration (counted as 0).

Accuracy per tier, incl. sealed

Radar: accuracy per tier, incl. sealed, two systemsAccuracy per tier, incl. sealed, GLiNER2 vs Jev 1.13.0. Easy: 97% vs 100%; Standard: 67% vs 99%; Judge: 46% vs 95%; Hard: 36% vs 74%; Sealed: 29% vs 37%.50100Easy97% · 100%Standard67% · 99%Judge46% · 95%Hard36% · 74%Sealed29% · 37%
Share correct per tier; Sealed = the 308 private decisions, aggregate only.

Current question set by family (hard + sealed)

Radar: current question set by family (hard + sealed), two systemsCurrent question set by family (hard + sealed), GLiNER2 vs Jev 1.13.0. Ambiguous / abstain: 39% vs 43%; Judge: 45% vs 54%; Long policy: 24% vs 44%; Multi-hop: 32% vs 64%; Probability: 21% vs 63%; Temporal / numeric: 20% vs 28%; Trade-off: 42% vs 55%; Routing: 70% vs 100%; Trap / adversarial: 38% vs 83%; Paraphrase: 14% vs 64%; Safety judge: 50% vs 38%.50100Ambiguous /abstain39% · 43%Judge45% · 54%Long policy24% · 44%Multi-hop32% · 64%Probability21% · 63%Temporal /numeric20% · 28%Trade-off42% · 55%Routing70% · 100%Trap /adversarial38% · 83%Paraphrase14% · 64%Safety judge50% · 38%
Share correct per family across the 220 hard-tier decisions (public and held out) and the 308 sealed decisions of v1.4, pooled; Routing is hard-tier only, Paraphrase and Safety judge sealed only.

Sealed set by family

Radar: sealed set by family, two systemsSealed set by family, GLiNER2 vs Jev 1.13.0. Ambiguous / abstain: 41% vs 30%; Judge: 44% vs 34%; Long policy: 23% vs 28%; Multi-hop: 26% vs 45%; Paraphrase: 14% vs 64%; Probability: 14% vs 50%; Safety judge: 50% vs 38%; Temporal / numeric: 20% vs 29%; Trade-off: 38% vs 38%; Trap / adversarial: 25% vs 42%.50100Ambiguous /abstain41% · 30%Judge44% · 34%Long policy23% · 28%Multi-hop26% · 45%Paraphrase14% · 64%Probability14% · 50%Safety judge50% · 38%Temporal /numeric20% · 29%Trade-off38% · 38%Trap /adversarial25% · 42%
Share correct within each sealed family — system-level aggregates; the items stay private.

Availability and evidence

Openness
Code and weights marked open in the published row
License note
Apache-2.0
Cost evidence
estimated; the board’s row disclosure contains the published basis.
Endpoint condition
our CPU (4 threads, Ryzen 5 3600)
Note on this row
A general schema classifier, not a Jev rebuild. The question goes in front of the text; the probabilities are GLiNER2's own single-label softmax over the labels, read out in full (mapping fixed before the run).
Published source
https://github.com/fastino-ai/GLiNER2

From the public v1.4.2.2 aggregate. Scores and ranks can change when a new release is published.

Read the full board and published method. The overall score is a composite, not raw accuracy.