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JevBench by Benchmark Heaven · v1.4.2.2 · individual system

djev (Maisa, diffusion-gemma)

Jev rebuild · by Maisa (David Villalón)

JevBench v1.4.2.2 score

52.2

Rank #10 of 91 ranked systems.

11.1 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
47.0
calibration
55.4
speed
91.4
cost
57.6

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: djev — Jev rebuild · Score 52.2 (#10)
  • 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, djev vs Jev 1.13.0. Intelligence: 47.0 vs 53.1; Calibration: 55.4 vs 76.3; Speed: 91.4 vs 83.3; Cost: 57.6 vs 52.0.50100Intelligence47.0 · 53.1Calibration55.4 · 76.3Speed91.4 · 83.3Cost57.6 · 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, djev vs Jev 1.13.0. Easy: 100% vs 100%; Standard: 98% vs 99%; Judge: 93% vs 95%; Hard: 70% vs 74%; Sealed: 30% vs 37%.50100Easy100% · 100%Standard98% · 99%Judge93% · 95%Hard70% · 74%Sealed30% · 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), djev vs Jev 1.13.0. Ambiguous / abstain: 33% vs 43%; Judge: 66% vs 54%; Long policy: 35% vs 44%; Multi-hop: 56% vs 64%; Probability: 40% vs 63%; Temporal / numeric: 27% vs 28%; Trade-off: 42% vs 55%; Routing: 100% vs 100%; Trap / adversarial: 78% vs 83%; Paraphrase: 43% vs 64%; Safety judge: 38% vs 38%.50100Ambiguous /abstain33% · 43%Judge66% · 54%Long policy35% · 44%Multi-hop56% · 64%Probability40% · 63%Temporal /numeric27% · 28%Trade-off42% · 55%Routing100% · 100%Trap /adversarial78% · 83%Paraphrase43% · 64%Safety judge38% · 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, djev vs Jev 1.13.0. Ambiguous / abstain: 19% vs 30%; Judge: 49% vs 34%; Long policy: 23% vs 28%; Multi-hop: 32% vs 45%; Paraphrase: 43% vs 64%; Probability: 25% vs 50%; Safety judge: 38% vs 38%; Temporal / numeric: 23% vs 29%; Trade-off: 31% vs 38%; Trap / adversarial: 33% vs 42%.50100Ambiguous /abstain19% · 30%Judge49% · 34%Long policy23% · 28%Multi-hop32% · 45%Paraphrase43% · 64%Probability25% · 50%Safety judge38% · 38%Temporal /numeric23% · 29%Trade-off31% · 38%Trap /adversarial33% · 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 code; Google DiffusionGemma Apache-2.0 weights; no djev-specific weights
Cost evidence
announced price; the board’s row disclosure contains the published basis.
Endpoint condition
production API (api.djev.dev, free preview)
Note on this row
The measured endpoint was Maisa's hosted API in free preview; the cost uses its announced price ($0.035 per million input tokens, output free), and nothing was charged. The self-hostable djev-dev runtime is Apache-2.0 and applies a structured one-step inference method to Google's Apache-2.0 diffusiongemma-26B-A4B-it checkpoint; it adds no separately trained djev weights. Probabilities are djev's own (its docs call them experimental and uncalibrated). v1.4: hosted api.djev.dev was paused by its operator ("Serving is paused by the administrator"); sealed tier measured on the public djev runtime (Davipar/djev-dev 3ce907e, same weights, default mode) self-hosted on an H100; Speed/Cost kept from v1.3.
Published source
https://github.com/Davipar/djev-dev

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.