MODEL PROFILE

Qwen3.5-4B-Heretic-GGUF

darrellbest · Qwen3.5-4B-Heretic-GGUF

GGUF builds of darrellbest/Qwen3.5-4B-Heretic. Qwen/Qwen3.5-4B with its refusal behaviour removed by Heretic using full-weight Arbitrary-Rank Ablation: **6/100 refusals** (original: 99/100) at **KL divergence 0.0220**. See the main repository for how it was made and measured. Converted from the bf16 safetensors with llama.cpp's `convert_hf_to_gguf.py` and quantized with `llama-quantize` (no imatrix). The mmproj file carries the vision encoder; load it alongside any of the three for image input. Every file was loaded in `llama-server` with the mmproj and in Ollama. All three answered ordinary prompts correctly (BF16 and Q8_0 reproduce each other word for word), described a test image (a red circle and a blue square) correctly, and in Ollama answered 17 x 23 = 391 with thinking off. Thinking-mode reasoning, 4 arithmetic and word problems x 10 seeds with Qwen's recommended sampling: BF16 39/40, Q8_0 40/40, Q4_K_M 40/40 finished and correct (the original model in vLLM: 40/40).

Visual QAlicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/10/30 14:55:28
OVERVIEW

Model overview

GGUF builds of darrellbest/Qwen3.5-4B-Heretic. Qwen/Qwen3.5-4B with its refusal behaviour removed by Heretic using full-weight Arbitrary-Rank Ablation: **6/100 refusals** (original: 99/100) at **KL divergence 0.0220**. See the main repository for how it was made and measured. Converted from the bf16 safetensors with llama.cpp's `convert_hf_to_gguf.py` and quantized with `llama-quantize` (no imatrix). The mmproj file carries the vision encoder; load it alongside any of the three for image input. Every file was loaded in `llama-server` with the mmproj and in Ollama. All three answered ordinary prompts correctly (BF16 and Q8_0 reproduce each other word for word), described a test image (a red circle and a blue square) correctly, and in Ollama answered 17 x 23 = 391 with thinking off. Thinking-mode reasoning, 4 arithmetic and word problems x 10 seeds with Qwen's recommended sampling: BF16 39/40, Q8_0 40/40, Q4_K_M 40/40 finished and correct (the original model in vLLM: 40/40).

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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Estimate monthly base token costs

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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。

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Frequently asked questions

Do open weights permit free commercial use?

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Sources & traceability

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。