Model overview
**Uncensored 552B MoE with 1M-token context, vision, and full tool/reasoning support — converted to GGUF for llama.cpp.** Built from `dealignai/DeepSeek-V4.1-Flash-UNCENSORED-FP8` (permanent weight-level abliteration of `deepseek-ai/DeepSeek-V4.1-Flash`), converted to GGUF and requantized. **No guardrails: the model follows on prompts the base model refuses (verified, see Benchmarks).** > ## ✅ Update 2026-10-15 — corrected re-quants are live > > **The Q3_K_M and Q4_K_M files on the Hub have been replaced** with corrected re-quants built from the Q8_0 bridge using the corrected per-layer ramp (see below). If you downloaded Q3 or Q4 earlier, the files have changed — re-download. > > - **Q3_K_M:** now **352 GB (9 × ≤50 GB shards)** — 23 GB smaller than the previous build, identical measured quality at every benchmark we ran on both. > - **Q4_K_M:** now **426 GB (3 shards)** — routed experts are pure Q4_K as the tier name says (the previous build re-encoded the checkpoint-native MXFP4 experts into Q4_K/Q5_K, which is what the audit flagged). > - **Q2_K:** rebuilt (v3) — now pins the indexer/hyperconn layers per the recipe (the previous build left them at base precision). Same size class, files replaced on the Hub. The benchmark table below is measured on v3; the 1M NIAH tier on v3 is running. > - **Q8_0:** unchanged — still the reference bridge. > > Details: Per-group quantization & size · Benchmarks
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.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
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。
View full indexed rankings →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
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。