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AI Model Library/richardyoung/DeepSeek-R1-0528-Qwen3-8B-heretic-GGUF
MODEL PROFILE

DeepSeek-R1-0528-Qwen3-8B-heretic-GGUF

richardyoung · DeepSeek-R1-0528-Qwen3-8B-heretic-GGUF

GGUF quantizations of richardyoung/DeepSeek-R1-0528-Qwen3-8B-heretic, an abliterated build of deepseek-ai/DeepSeek-R1-0528-Qwen3-8B (DeepSeek's R1-0528 reasoning distilled into Qwen3-8B: a reasoning model that emits chains before answering) made with Heretic. The very low KL divergence (0.041, far below the 0.5 “damage” threshold) means the model retains essentially all of its original capabilities and coherence. Each quant compared with the F16 model using `llama-perplexity --kl-divergence` on the wikitext-2 test set (40 × 512-token chunks). KL divergence measures how far the quant's next-token probabilities drift from F16; lower is better. Top-token match is how often the quant picks the same next token as F16. As a rough guide, a KLD under 0.01 is hard to tell from F16, and from about 0.05 differences start to show in longer outputs.

Text generationlicense:mit
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/31 04:06:45
OVERVIEW

Model overview

GGUF quantizations of richardyoung/DeepSeek-R1-0528-Qwen3-8B-heretic, an abliterated build of deepseek-ai/DeepSeek-R1-0528-Qwen3-8B (DeepSeek's R1-0528 reasoning distilled into Qwen3-8B: a reasoning model that emits chains before answering) made with Heretic. The very low KL divergence (0.041, far below the 0.5 “damage” threshold) means the model retains essentially all of its original capabilities and coherence. Each quant compared with the F16 model using `llama-perplexity --kl-divergence` on the wikitext-2 test set (40 × 512-token chunks). KL divergence measures how far the quant's next-token probabilities drift from F16; lower is better. Top-token match is how often the quant picks the same next token as F16. As a rough guide, a KLD under 0.01 is hard to tell from F16, and from about 0.05 differences start to show in longer outputs.

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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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?

Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.

Are these real-time billing prices?

These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.

Sources & traceability

huggingface · richardyoung/DeepSeek-R1-0528-Qwen3-8B-heretic-GGUF ↗2026/10/30 12:10:33
huggingface · enrich:fdd15fb0-ff42-44f3-b831-b21df734dd1f ↗2026/10/31 04:06:45

许可证：mit。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。