spark-s1-4b-v6 (Open Spark Jev, abhishek085)
Jev rebuild · by Abhishek Rai (abhishek085)
JevBench v1.4.2.2 score
44.6
Rank #17 of 91 ranked systems.
18.7 points behind Jev 1.13.0's 63.3.
Published axes
- intelligence
- 45.1
- calibration
- 47.6
- speed
- 81.0
- cost
- 57.9
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: spark-s1-4b-v6 — Jev rebuild · Score 44.6 (#17)
- B: Jev 1.13.0 — Jev (TypeSafe, closed) · Score 63.3 (#4)
The four score axes
Accuracy per tier, incl. sealed
Current question set by family (hard + sealed)
Sealed set by family
Availability and evidence
- Openness
- Code and weights marked open in the published row
- License note
- Apache-2.0 (code and weights); base Qwen/Qwen3.5-4B Apache-2.0
- Cost evidence
- estimated; the board’s row disclosure contains the published basis.
- Endpoint condition
- our RunPod GPU (L40 48 GB, Czechia), reached over the internet from Germany
- Note on this row
- Abhishek085/spark-s1-4b-v6 revision 93d49ddbfb29212e3296635a75a3e80cf69da027, code github.com/abhishek085/open-spark-jev 30ac6d89b7fa36c644cf86aac68f35c1d276a919, the author's own MenuScorer.decide with his fitted calibration.json temperature, bf16, base Qwen/Qwen3.5-4B, transformers 5.17.0 / torch 2.8.0 from the pod image, flash-linear-attention 0.5.2 installed, causal_conv1d not installable here (no wheel builds against this toolchain), on our RunPod L40 in Czechia Offline local open-weight inference on the frozen 308-item v1.4 set in a network-disabled, read-only container; no operator endpoint received sealed text.
- Published source
- https://github.com/abhishek085/open-spark-jev
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.