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AI 模型库/Jommarn/UNSEEN_Gemma_4_26B_NSFW-GGUF
MODEL PROFILE · 模型档案

UNSEEN_Gemma_4_26B_NSFW-GGUF

Jommarn · UNSEEN_Gemma_4_26B_NSFW-GGUF

> 📌 **Base Model:** The full unquantized FP16/BF16 weights are hosted at 👉 **Jommarn/UNSEEN_Gemma_4_26B_NSFW** (surgically abliterated from `google/gemma-4-26B-A4B-it`). > > ⚡ **This Repository:** Dedicated to optimized **Quantized (2-bit / 3-bit / 4-bit / 5-bit / 6-bit / 8-bit / 16-bit Master)** and **GGUF** deployment formats for consumer GPUs, Apple Silicon Mac, and `llama.cpp` serving. - **2-bit (`IQ2_M` ~9.67GB):** ~8–10GB VRAM (e.g., RTX 3060 12GB, RTX 4060, Mac 16GB) — *Extreme Efficiency* - **3-bit (`IQ3_M` ~12.4GB):** ~12–14GB VRAM (e.g., RTX 4070 12GB, RTX 3080, Mac 16GB) — *High Efficiency* - **4-bit (`Q4_K_M` ~15.6GB / `NF4`):** ~16–18GB VRAM (e.g., RTX 3090, RTX 4090, NVIDIA L4) — *Recommended Standard* - **5-bit (`Q5_K_M` ~18.3GB):** ~20–22GB VRAM (e.g., RTX 3090/4090 24GB, A10G 24GB) — *Balanced High-Quality* - **6-bit (`Q6_K` ~22.6GB):** ~24–26GB VRAM (e.g., RTX 4090 24GB, A100 40GB) — *High Precision* - **8-bit (`Q8_0` ~28.0GB / `INT8`):** ~28–30GB VRAM (e.g., 2x RTX 3090/4090, A100 40GB/80GB) — *99.9% Lossless* - **16-bit (`BF16` ~50.5GB):** ~52GB VRAM (e.g., A100 80GB, Mac Studio 64GB/128GB) — *100% Uncompressed Master* - **Vision Projector (16-bit):** `mmproj-gemma4-vision-f16.gguf` (~1.11GB) — *Must be loaded with `--mmproj` for image perception in llama.cpp/GGUF.* - **GGUF Weights:** Available at 👉 **Jommarn/UNSEEN_Gemma_4_26B_NSFW-GGUF** > ⚠️ **Important for GGUF Users:** To enable image understanding in `llama.cpp` or LM Studio, you **MUST** download and pass `mmproj-gemma4-vision-f16.gguf` alongside the main model. Without it, the model will operate strictly as a text-only LLM!

译文排队中，当前展示来源原文。

视觉问答
上下文窗口来源未披露
输入 → 输出文本、图像 → 文本
模型权重待核验
档案更新时间2026/11/2 19:17:17
OVERVIEW

模型介绍

> 📌 **Base Model:** The full unquantized FP16/BF16 weights are hosted at 👉 **Jommarn/UNSEEN_Gemma_4_26B_NSFW** (surgically abliterated from `google/gemma-4-26B-A4B-it`). > > ⚡ **This Repository:** Dedicated to optimized **Quantized (2-bit / 3-bit / 4-bit / 5-bit / 6-bit / 8-bit / 16-bit Master)** and **GGUF** deployment formats for consumer GPUs, Apple Silicon Mac, and `llama.cpp` serving. - **2-bit (`IQ2_M` ~9.67GB):** ~8–10GB VRAM (e.g., RTX 3060 12GB, RTX 4060, Mac 16GB) — *Extreme Efficiency* - **3-bit (`IQ3_M` ~12.4GB):** ~12–14GB VRAM (e.g., RTX 4070 12GB, RTX 3080, Mac 16GB) — *High Efficiency* - **4-bit (`Q4_K_M` ~15.6GB / `NF4`):** ~16–18GB VRAM (e.g., RTX 3090, RTX 4090, NVIDIA L4) — *Recommended Standard* - **5-bit (`Q5_K_M` ~18.3GB):** ~20–22GB VRAM (e.g., RTX 3090/4090 24GB, A10G 24GB) — *Balanced High-Quality* - **6-bit (`Q6_K` ~22.6GB):** ~24–26GB VRAM (e.g., RTX 4090 24GB, A100 40GB) — *High Precision* - **8-bit (`Q8_0` ~28.0GB / `INT8`):** ~28–30GB VRAM (e.g., 2x RTX 3090/4090, A100 40GB/80GB) — *99.9% Lossless* - **16-bit (`BF16` ~50.5GB):** ~52GB VRAM (e.g., A100 80GB, Mac Studio 64GB/128GB) — *100% Uncompressed Master* - **Vision Projector (16-bit):** `mmproj-gemma4-vision-f16.gguf` (~1.11GB) — *Must be loaded with `--mmproj` for image perception in llama.cpp/GGUF.* - **GGUF Weights:** Available at 👉 **Jommarn/UNSEEN_Gemma_4_26B_NSFW-GGUF** > ⚠️ **Important for GGUF Users:** To enable image understanding in `llama.cpp` or LM Studio, you **MUST** download and pass `mmproj-gemma4-vision-f16.gguf` alongside the main model. Without it, the model will operate strictly as a text-only LLM!

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价，请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用？

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗？

不是实时结算价格，而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

huggingface · Jommarn/UNSEEN_Gemma_4_26B_NSFW-GGUF ↗2026/10/31 20:52:23
huggingface · enrich:40179a83-f413-4930-92cf-4704855048ec ↗2026/10/29 18:41:12

许可证：来源未披露，须进一步核验。模型介绍与第三方评测均以原来源的具体版本和方法为准。