JevK5 4B — VRAM & /v1/systemone setup
Written by Jakub Rusinowski · Last updated
A 4B decision model on Qwen3.5-4B-Base with a TypeSafe-style server; English only, and inputs over 16,384 tokens are refused rather than cut.
JevK5 4B needs about 4 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.
Call JevK5 4B
Served by jevk5-serve (default port 8090). This model does not run in Ollama.
http://localhost:8090/v1/systemone
Setup for servers other than Ollama →
Build a request for this model Decision models guide
Other decision models: Nimble 9B · Tev1 4B · Tev1 0.8B · Winnow 12B · Winnow E4B · Decider 2B · Decider 4B · Decider 35B-A3B (NVFP4) · Intern-Decision 4B · AutoJev 27B · Laya
Hardware fit
Weights plus overhead plus the KV cache at a 16,384-token prompt, on NVIDIA RTX 4090 (24 GB). A publisher build is sized from its file; the other rows are modelled at a standard quant. Decision requests are short, so no long-context figure is shown.
| Quant | Memory | VRAM | Fit |
|---|---|---|---|
| BF16 Publisher build · 9 GB file | 11.7 GB | Fits | |
| Q4_K_M 4.83 bpw · modelled quant | 5.6 GB | Fits | |
| Q6_K 6.56 bpw · modelled quant | 6.6 GB | Fits | |
| Q8_0 8.50 bpw · modelled quant | 7.7 GB | Fits |
Published file size: BF16 9 GB. A download size from the model publisher — not a VRAM requirement.
English only. Inputs over 16,384 tokens refused, not cut. Server: jevk5-serve --model alibiserikbay/JevK5 --port 8090. GGUF Q8_0/Q4_K_M in JevK5-GGUF.
How it was scored
Two different suites on two different scales. Never compare the numbers across the two cards.
Decision Index 0.2.1 (snapshot 2026-09-28)
Decision Index 0.2.1- ECE (lower is better)
- 0.0268
- Median compute
- 22 ms on 1x NVIDIA RTX PRO 6000 (96 GB)
Community-maintained; not affiliated with the model authors.
Source ↗Decision models are not ranked on chat, creative or coding scores.
Specifications
Verified — Checked against the primary source — the model card or the vendor spec page — and corroborated by a second independent source. Still unconfirmed: weightsGbByQuant.
- Parameters
- 4.66B
- Context window
- 16K (prompt limit)
- Architecture
- Fine-tune of Qwen/Qwen3.5-4B-Base
- Provider
- alibiserikbay
- Licence
- Apache-2.0
- Specified at
- Q4_K_M
- System RAM
- 8 GB
- Record updated
- 2026-09-30
Commercial use permitted. No usage restrictions beyond attribution.
JevK5 4B — frequently asked questions
What is JevK5 4B?
JevK5 4B is a decision model: you send it a state and typed questions (choice, yes/no/unknown, or a score) and it returns one answer per question with a probability for every option. It is not a chat model.
How do I run JevK5 4B locally?
JevK5 4B does not run in Ollama. Served by jevk5-serve (default port 8090). This model does not run in Ollama. See the setup guide for servers other than Ollama.
How much memory does JevK5 4B need?
About 4 GB for the weights plus overhead at Q4_K_M, before the prompt's KV cache. Decision prompts are short, so the cache stays small.
How accurate is JevK5 4B?
It has two separate published scores on two different suites — the author's own benchmark and the community Decision Index 0.2.1. They are not comparable with each other, and neither is a calibration guarantee.