Hanno Labs1.7B~2 GB VRAM at Q4_K_M

Bosun v3.1 1.7B — VRAM & /v1/systemone setup

Written by Jakub Rusinowski · Last updated

Hanno Labs' 1.7B decision model: a rank-16 LoRA on Qwen3-1.7B with 256 decision tokens, up to 255 candidates a question. Served by the Jev-compatible server at /v1/systemone.

Bosun v3.1 1.7B needs about 2 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 Bosun v3.1 1.7B

Served by jev-compatible-server (default port 8000). This model does not run in Ollama.

Question types
choice noul (yes / no) score
Inputs
text
Max candidates per question
255
Serve with
jev-compatible-server
Endpoint
/v1/systemone
Languages
English
uvx --from 'jev-compatible-server[transformers]' jev-compatible-server --model bosun-v3.1-1.7b

http://localhost:8000/v1/systemone

Setup for servers other than Ollama →

Weights on Hugging Face: Hanno-Labs/bosun-v3.1-1.7b ↗

Build a request for this model Decision models guide

Related guides: Confidence, thresholds and calibration · Servers other than Ollama

Other decision models: Nimble 9B · Tev1 4B · Tev1 0.8B · Winnow 12B · Winnow E4B · Decider 2B · Decider 4B · Decider 35B-A3B (NVFP4) · JevK5 4B · Intern-Decision 4B · AutoJev 27B · Laya · Clef 27B · Clef-Flash 9B · Rune 26B-A4B v3 · OpenDecider-nano · OpenDecider-small · OpenDecider-small MLX 4-bit · Bosun v3.1 0.6B · d1-3B · d1-omni-600M · THX-01 322M

Hardware fit

Weights plus overhead plus the KV cache at a 8,192-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.

QuantVRAMFit
Q5_K_M
Publisher build · 1.26 GB file
2.8 GBFits
BF16 (base + adapter)
Publisher build · 4.15 GB file
5.7 GBFits
Q4_K_M
4.83 bpw · modelled quant
2.8 GBFits
Q6_K
6.56 bpw · modelled quant
3.2 GBFits
Q8_0
8.50 bpw · modelled quant
3.4 GBFits

Published file size: Q5_K_M 1.26 GB · Q8_0 1.83 GB · BF16 (base + adapter) 4.15 GB. A download size from the model publisher — not a VRAM requirement.

How it was scored

Each table is one suite. Numbers in different tables were measured on different questions and are not comparable, with each other or with the Decision Index.

Decision Index 0.2.1 (snapshot 2026-09-28)

Decision Index 0.2.1Community Decision Index (not by the model's authors)
Balanced skill20.1
ECE (lower is better)
0.1302
Median compute
40.3 ms on 1x NVIDIA RTX PRO 6000 (96 GB)

Community-maintained; not affiliated with the model authors.

Source ↗
DecisionBench 1.0 (Hanno Labs) — Benchmark built by the same team that built this model
What was scoredScoreECENLLCoverageSource
Applied suite (22,700 rows)87.29%0.03970.4328100%Source ↗
All rows, including the 1,200-row reasoning track (23,900 rows)84.9%0.04970.4776100%Source ↗

The authors' caveat: these are held-out rows from task families represented in Bosun's training data, not evidence on unseen task families.

On the separate reasoning track, Jev leads both Bosun models (the authors’ statement).

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.

Parameters
2.03B
Context window
Not published
Architecture
Fine-tune of Qwen/Qwen3-1.7B
Provider
Hanno Labs
Licence
Apache-2.0
Availability
Weights downloadable
Practical deployment
Edge device (phone, SBC)
Specified at
Q4_K_M
System RAM
8 GB
Record updated
2026-10-13
LicenceApache-2.0Commercial use permitted

Commercial use permitted. No usage restrictions beyond attribution.

Other Bosun sizes

Bosun v3.1 1.7B — frequently asked questions

What is Bosun v3.1 1.7B?

Bosun v3.1 1.7B 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 Bosun v3.1 1.7B locally?

Served by jev-compatible-server (default port 8000). This model does not run in Ollama. Start it with: `uvx --from 'jev-compatible-server[transformers]' jev-compatible-server --model bosun-v3.1-1.7b`.

How much memory does Bosun v3.1 1.7B need?

About 2 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 Bosun v3.1 1.7B?

It has separate published scores on different suites — the community Decision Index 0.2.1 and the benchmarks listed on this page. They are not comparable with each other, and none is a calibration guarantee.