JevBench by Benchmark Heaven · v1.4.2.2 · individual system

JevAct (einptein, jev1-2b-v2)

Jev rebuild · by einptein · API endpoint saw sealed item text

JevBench v1.4.2.2 score

16.9

Rank #67 of 91 ranked systems.

46.4 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
29.3
calibration
55.1
speed
76.5
cost
64.3

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: JevAct — Jev rebuild · Score 16.9 (#67)
  • 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, JevAct vs Jev 1.13.0. Intelligence: 29.3 vs 53.1; Calibration: 55.1 vs 76.3; Speed: 76.5 vs 83.3; Cost: 64.3 vs 52.0.50100Intelligence29.3 · 53.1Calibration55.1 · 76.3Speed76.5 · 83.3Cost64.3 · 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, JevAct vs Jev 1.13.0. Easy: 99% vs 100%; Standard: 69% vs 99%; Judge: 59% vs 95%; Hard: 37% vs 74%; Sealed: 23% vs 37%.50100Easy99% · 100%Standard69% · 99%Judge59% · 95%Hard37% · 74%Sealed23% · 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), JevAct vs Jev 1.13.0. Ambiguous / abstain: 31% vs 43%; Judge: 46% vs 54%; Long policy: 0% vs 44%; Multi-hop: 12% vs 64%; Probability: 29% vs 63%; Temporal / numeric: 24% vs 28%; Trade-off: 34% vs 55%; Routing: 90% vs 100%; Trap / adversarial: 78% vs 83%; Paraphrase: 14% vs 64%; Safety judge: 31% vs 38%.50100Ambiguous /abstain31% · 43%Judge46% · 54%Long policy0% · 44%Multi-hop12% · 64%Probability29% · 63%Temporal /numeric24% · 28%Trade-off34% · 55%Routing90% · 100%Trap /adversarial78% · 83%Paraphrase14% · 64%Safety judge31% · 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, JevAct vs Jev 1.13.0. Ambiguous / abstain: 27% vs 30%; Judge: 34% vs 34%; Long policy: 0% vs 28%; Multi-hop: 21% vs 45%; Paraphrase: 14% vs 64%; Probability: 21% vs 50%; Safety judge: 31% vs 38%; Temporal / numeric: 23% vs 29%; Trade-off: 23% vs 38%; Trap / adversarial: 67% vs 42%.50100Ambiguous /abstain27% · 30%Judge34% · 34%Long policy0% · 28%Multi-hop21% · 45%Paraphrase14% · 64%Probability21% · 50%Safety judge31% · 38%Temporal /numeric23% · 29%Trade-off23% · 38%Trap /adversarial67% · 42%
Share correct within each sealed family — system-level aggregates; the items stay private.

Availability and evidence

Openness
Marked closed in the published row
License note
not stated (the author published only an endpoint and the evaluation client)
Cost evidence
estimated; the board’s row disclosure contains the published basis.
Endpoint condition
author-hosted endpoint (one machine at 115.190.124.200:18084, China), reached from a Hetzner server in Germany
Note on this row
Requested in GitHub issue #66. The author published an endpoint and an evaluation client, not weights, and his API is not the TypeSafe wire format, so JevBench's own `jevact_api` adapter implements exactly the mapping table in his eval_code.zip: state to state, instructions to the question, the labels with their criteria text as the options in label order, noul as false/true, and results[0].options[i].probability read back as the probability of labels[i] by index. His server answers HTTP 400 with `all inference items exceeded max_context_tokens or contained reserved markers` for an input it cannot take, and his own client and test script record exactly that as one failed item and continue; the adapter therefore surfaces that one documented refusal as the harness's 422 refusal path, which scores it as a wrong answer and does not count toward the stop rule - the same treatment the swanOne and Cygnet packages get for their own 422. Any other 400 or an outage still stops the run. The endpoint reports no token accounting, so cost is the labelled 2B size-class estimate. The endpoint is one machine in China and the latency includes that distance; it is not a production API and gets the standard x2 self-host adjustment, without the +0.15 s that only our own servers carry. 237/308 sealed items answered validly (failures count as wrong)
Published source
https://github.com/fstandhartinger/jevbench/issues/66

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.