Rune 26B-A4B v3 — VRAM & local setup
作者： Jakub Rusinowski · 最后更新：
Surogate 基于 Gemma 4 26B-A4B 的 26B 混合专家决策模型（4B 激活），支持图像输入。在 2026 年 9 月 28 日的 Decision Index 0.2.1 快照中是得分最高的可下载模型；由 surogate serve 提供服务。
Rune 26B-A4B v3 在 Q4_K_M 下约需 16 GB 显存——量化权重加框架开销，不含 KV 缓存。在 Apple Silicon 上，这部分来自统一内存。
Call Rune 26B-A4B v3
Served by surogate serve. This model does not run in Ollama.
- Question types
- choice noul (yes / no) score
- Inputs
- text image
- Serve with
surogate serve- Endpoint
/v1/decisions
Setup for servers other than Ollama →
Not in the request builder: Surogate serves POST /v1/decisions, and the builder writes /v1/systemone requests.
Related guides: Confidence, thresholds and calibration · Decision models on images · 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 · OpenDecider-nano · OpenDecider-small · OpenDecider-small MLX 4-bit · Bosun v3.1 0.6B · Bosun v3.1 1.7B · 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. Image tokens are not modelled: each image adds to the prompt, so a request with images needs more memory than these rows.
| 量化 | 显存 | 显存 | 适配 |
|---|---|---|---|
| BF16 Publisher build · 51.6 GB file | 54.1 GB | 需卸载 | |
| Q4_K_M 4.83 bpw · modelled quant | 18.1 GB | 可运行 | |
| Q6_K 6.56 bpw · modelled quant | 23.7 GB | 勉强 | |
| Q8_0 8.50 bpw · modelled quant | 29.9 GB | 需卸载 |
Published file size: BF16 51.6 GB. A download size from the model publisher — not a VRAM requirement.
The repository is named “-GGUF” but holds BF16 safetensors (11 shards, 51.6 GB), and it is gated: accept its terms on Hugging Face before downloading. The Decision Index served it with surogate serve (v1.5.3) at POST /v1/decisions, not /v1/systemone. The model card could not be read, so its context length, thinking mode and calibration controls are not listed here.
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 0.2.1Community Decision Index (not by the model's authors)- ECE (lower is better)
- 0.1196
- Median compute
- 120.5 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.
规格
Verified — Checked against the primary source — the model card or the vendor spec page — and corroborated by a second independent source. 尚未确认： questionTypes, activeParameters, contextWindow.
- 参数量
- 25.81B
- 上下文窗口
- Not published
- 架构
- Fine-tune of google/gemma-4-26B-A4B-it (mixture-of-experts)
- 提供商
- Surogate
- 许可证
- Apache-2.0
- Availability
- Weights downloadable
- Practical deployment
- Single consumer GPU
- 规格量化
- Q4_K_M
- 系统内存
- 34 GB
- 记录更新于
- 2026-10-13
Commercial use permitted. No usage restrictions beyond attribution.
Rune 26B-A4B v3 — 常见问题
What is Rune 26B-A4B v3?
Rune 26B-A4B v3 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 Rune 26B-A4B v3 locally?
Served by surogate serve. This model does not run in Ollama.
How much memory does Rune 26B-A4B v3 need?
About 16 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 Rune 26B-A4B v3?
Its published score is on the community Decision Index 0.2.1, which its authors did not build. It is not a calibration guarantee: test on your own examples.