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akhilaaa3Open weights model12B parameters

Jev-Omni benchmarks

All models
  • General rank
    Too few tasks3 non-coding tasks ranked5 needed for a rank
  • Speed#4 / 7
    248 msMedian latency, p50H100 only
  • Cost
    Self-hostedRan on H100No hosted price
  • LLM-as-a-judge#1 / 20 tied
    72.0%Best task · Accuracyvs Jev-class models

Comparison summary

Strongest
Judging and evals
Leads 3 of 3 (100%)

Strong at judging. It is ranked on 3 non-coding tasks, too few for a general rank (5 needed).

Specifications

Lab
akhilaaa3
Weights
Open weights
Parameters
12B
Licence
Apache-2.0

Judging and evals

Share of tasks led · #4 of 20

  1. ClefLeads 3 of 3
  2. Decision 2.0 Vega 27BLeads 3 of 3
  3. GLiDELeads 3 of 3
  4. Jev-Omni
    Leads 3 of 3
  5. Kev-27BLeads 3 of 3
  6. WinnowLeads 3 of 3
  7. JevLeads 3 of 6
  8. DiffusionGemma-JevLeads 1 of 3
See the 3 tasks

LLM-as-a-judge

Tied for the lead#1 / 20

Accuracy, % · Higher is better

  1. Decision 2.0 Vega 27B75.5, interval 69.8 to 81.3, tied for the lead
  2. Clef73.0, interval 66.2 to 79.7, tied for the lead
  3. Jev72.5, interval 66.7 to 78.3, tied for the lead
  4. GLiDE72.0, interval 65.7 to 78.1, tied for the lead
  5. Jev-Omni
    72.0, interval 65.5 to 78.5, tied for the lead
  6. Kev-27B72.0, interval 65.6 to 78.4, tied for the lead
  7. DiffusionGemma-Jev70.5, interval 63.8 to 77.4, tied for the lead
  8. Winnow70.5, interval 64.0 to 76.3, tied for the lead
Tested against Jev and 18 Jev-class models

Scenario judge

Tied for the lead#1 / 20

Accuracy, % · Higher is better

  1. Clef83.0, interval 77.4 to 88.4, tied for the lead
  2. Decision 2.0 Vega 27B81.0, interval 75.5 to 86.1, tied for the lead
  3. GLiDE79.5, interval 74.4 to 84.7, tied for the lead
  4. Winnow79.0, interval 73.1 to 85.0, tied for the lead
  5. Kev-27B78.0, interval 71.6 to 84.0, tied for the lead
  6. Jev76.5, interval 70.4 to 82.1, tied for the lead
  7. Hopper 12B75.5, interval 69.5 to 81.5, tied for the lead
  8. Jev-Omni
    75.5, interval 69.3 to 81.7, tied for the lead
Tested against Jev and 18 Jev-class models

Search

Tied for the lead#1 / 20

Accuracy, % · Higher is better

  1. Jev-Omni
    72.5, interval 65.7 to 78.7, tied for the lead
  2. GLiDE71.5, interval 64.4 to 77.8, tied for the lead
  3. Decision 2.0 Vega 27B71.0, interval 64.5 to 77.0, tied for the lead
  4. Winnow69.5, interval 63.2 to 75.6, tied for the lead
  5. Jev69.0, interval 62.3 to 75.5, tied for the lead
  6. Clef67.5, interval 61.3 to 73.1, tied for the lead
  7. Kev-27B66.0, interval 59.7 to 71.8, tied for the lead
  8. DiffusionGemma-Jev63.0, interval 56.3 to 69.5, tier 2
Tested against Jev and 18 Jev-class models

Speed

Median latency, p50 · H100 only · lower is better

  1. Cygnet162 ms
  2. DiffusionGemma-Jev188 ms
  3. Decision 2.0 Lux 9B213 ms
  4. Jev-Omni
    248 ms
  5. Kev-27B318 ms
  6. Hopper 12B397 ms
  7. Decision 2.0 Vega 27B724 ms
How we count

A model leads a task when it is in the task's leading tie tier. Each task counts inside its own benchmark, against that benchmark's models; no score is averaged. An area chart shows the models ranked on at least 2 of the area's tasks in a benchmark this model is in too. The overall standing counts every non-coding tasks and needs 5 for a rank. Latency is compared only on one hardware tier.

Jev-OmniOther modelsWhisker: 95% interval