AI NEWS.ccAI正在发生 未来正在更新
♡ 我的收藏 0
AI 模型库/saidutta69/MiniCPM-V-4.7-1B-heretic
MODEL PROFILE · 模型档案

MiniCPM-V-4.7-1B-heretic

saidutta69 · MiniCPM-V-4.7-1B-heretic

A decensored variant of openbmb/MiniCPM-V-4.7-1B, produced with Heretic v1.4.0 (directional ablation / "abliteration"). Refusal behaviour is suppressed here via targeted weight edits to the attention output and MLP down-projections rather than fine-tuning, so the vision tower, the OCR and grounding behaviour, and the on-device footprint are left intact. > [!IMPORTANT] > **The GGUF here is fully multimodal — text *and* vision.** Most converted VL checkpoints in this > collection ship a text-only GGUF, because the converter silently drops the vision tower. > llama.cpp registers MiniCPM-V 4.7 properly, so the vision tower is shipped as a separate > projector file, `MiniCPM-V-4.7-1B-heretic-mmproj-F16.gguf` (1.11 GB), and the two files together are the model. > For image input you **must** load both — see Quickstart. Text-only use needs only > the main GGUF. Nothing is lost in the conversion: the text GGUF holds > 1,006,209,856 tensor elements, an exact match for the text tower in `model.safetensors`, and the > projector holds the vision tower and merger exactly. **Who this is for:** developers who want an uncensored vision-language model small enough to run on a phone. The text tower is 1.01B and the vision tower 0.55B, so 1.55B total — by far the smallest model in this collection that still sees images, and it answers instead of declining: refusals drop from 60/100 to 5/100. OpenBMB ships an iPhone app for this checkpoint, and the base model is claimed to substantially outperform Qwen3.5 0.8B on both overall score and inference efficiency. Best for on-device image Q&A, OCR, screenshot and document reading, visual grounding, and local vision agents. If you need text-only at this size, Qwen3.5-0.8B-heretic is the denser sibling; if you want a stronger text model, take the vision tower off the table entirely and use one of the 3B text models.

译文排队中，当前展示来源原文。

视觉问答multimodallicense:apache-2.0
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 19:16:07
OVERVIEW

模型介绍

A decensored variant of openbmb/MiniCPM-V-4.7-1B, produced with Heretic v1.4.0 (directional ablation / "abliteration"). Refusal behaviour is suppressed here via targeted weight edits to the attention output and MLP down-projections rather than fine-tuning, so the vision tower, the OCR and grounding behaviour, and the on-device footprint are left intact. > [!IMPORTANT] > **The GGUF here is fully multimodal — text *and* vision.** Most converted VL checkpoints in this > collection ship a text-only GGUF, because the converter silently drops the vision tower. > llama.cpp registers MiniCPM-V 4.7 properly, so the vision tower is shipped as a separate > projector file, `MiniCPM-V-4.7-1B-heretic-mmproj-F16.gguf` (1.11 GB), and the two files together are the model. > For image input you **must** load both — see Quickstart. Text-only use needs only > the main GGUF. Nothing is lost in the conversion: the text GGUF holds > 1,006,209,856 tensor elements, an exact match for the text tower in `model.safetensors`, and the > projector holds the vision tower and merger exactly. **Who this is for:** developers who want an uncensored vision-language model small enough to run on a phone. The text tower is 1.01B and the vision tower 0.55B, so 1.55B total — by far the smallest model in this collection that still sees images, and it answers instead of declining: refusals drop from 60/100 to 5/100. OpenBMB ships an iPhone app for this checkpoint, and the base model is claimed to substantially outperform Qwen3.5 0.8B on both overall score and inference efficiency. Best for on-device image Q&A, OCR, screenshot and document reading, visual grounding, and local vision agents. If you need text-only at this size, Qwen3.5-0.8B-heretic is the denser sibling; if you want a stronger text model, take the vision tower off the table entirely and use one of the 3B text models.

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 · saidutta69/MiniCPM-V-4.7-1B-heretic ↗2026/10/29 21:57:11
huggingface · enrich:8a39cf21-eb66-4303-b09a-3578a50275d1 ↗2026/10/30 14:03:34

许可证：apache-2.0。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。