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AI 模型库/AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-BF16
MODEL PROFILE · 模型档案

Qwen3.6-27B-AEON-Ultimate-Uncensored-BF16

AEON-7 · Qwen3.6-27B-AEON-Ultimate-Uncensored-BF16

> [!IMPORTANT] > **Superseded by Qwen3.8 — use this instead:** `AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-NVFP4-MIXED` > > **Operator recipes (Spark Dynamic DFlash lattice, TP=2, RTX):** `AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED` > > This Qwen3.6-27B card stays online for history and existing downloads. For new work, move to the Qwen3.8 Ultimate Uncensored NVFP4-MIXED release. That line is far superior in capability and reaches substantially more of what the architecture can do, with a more refined mixed quantization methodology (NVFP4 + FP8 lattice) than these older Qwen3.6 exports. > > Serve with the unified container: `ghcr.io/aeon-7/aeon-vllm-ultimate:latest` (Spark / GB10) or `ghcr.io/aeon-7/aeon-vllm-ultimate-rtx:latest` (RTX discrete). > **Deployment, operations & benchmarks → github.com/AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-DFlash** > > The GitHub repo is the source of truth for the production deployment guide, hardware-tuned docker-compose configs (DGX Spark NVFP4, A100/H100 BF16), full configuration reference, measured throughput benchmarks, and `AGENTS.md` — an operator's manual that pre-empts common stale-documentation traps for AI coding agents working on this stack. > **🆕 2026-05-01 — MTP head grafted in.** This repo now ships with the original `mtp.*` head (15 tensors, ~0.85 GB) restored from the `Qwen/Qwen3.6-27B` base. vLLM's `--speculative-config '{"method":"qwen3_5_mtp","num_speculative_tokens":3}'` works directly on the BF16 checkpoint with no extra steps. Measured on DGX Spark: **mean accepted length 3.3/3, P0 ≈ 90% acceptance, avg draft acceptance 78%** — comparable to the base model, confirming abliteration doesn't damage the model's top-K distribution that MTP relies on. Credit to `@tcclaviger` for the empirical finding (discussion #6) that MTP doesn't need retraining post-abliteration. **No retraining was performed.** The MTP head is the unmodified base — only the residual-stream-writing weights of the LM were orthogonalized in the original v8 abliteration pass; the MTP head is independent of that pathway.

译文排队中，当前展示来源原文。

文本生成multimodalreasoninglicense:apache-2.0
上下文窗口来源未披露
输入 → 输出文本 → 文本
模型权重待核验
档案更新时间2026/11/2 19:15:59
OVERVIEW

模型介绍

> [!IMPORTANT] > **Superseded by Qwen3.8 — use this instead:** `AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-NVFP4-MIXED` > > **Operator recipes (Spark Dynamic DFlash lattice, TP=2, RTX):** `AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED` > > This Qwen3.6-27B card stays online for history and existing downloads. For new work, move to the Qwen3.8 Ultimate Uncensored NVFP4-MIXED release. That line is far superior in capability and reaches substantially more of what the architecture can do, with a more refined mixed quantization methodology (NVFP4 + FP8 lattice) than these older Qwen3.6 exports. > > Serve with the unified container: `ghcr.io/aeon-7/aeon-vllm-ultimate:latest` (Spark / GB10) or `ghcr.io/aeon-7/aeon-vllm-ultimate-rtx:latest` (RTX discrete). > **Deployment, operations & benchmarks → github.com/AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-DFlash** > > The GitHub repo is the source of truth for the production deployment guide, hardware-tuned docker-compose configs (DGX Spark NVFP4, A100/H100 BF16), full configuration reference, measured throughput benchmarks, and `AGENTS.md` — an operator's manual that pre-empts common stale-documentation traps for AI coding agents working on this stack. > **🆕 2026-05-01 — MTP head grafted in.** This repo now ships with the original `mtp.*` head (15 tensors, ~0.85 GB) restored from the `Qwen/Qwen3.6-27B` base. vLLM's `--speculative-config '{"method":"qwen3_5_mtp","num_speculative_tokens":3}'` works directly on the BF16 checkpoint with no extra steps. Measured on DGX Spark: **mean accepted length 3.3/3, P0 ≈ 90% acceptance, avg draft acceptance 78%** — comparable to the base model, confirming abliteration doesn't damage the model's top-K distribution that MTP relies on. Credit to `@tcclaviger` for the empirical finding (discussion #6) that MTP doesn't need retraining post-abliteration. **No retraining was performed.** The MTP head is the unmodified base — only the residual-stream-writing weights of the LM were orthogonalized in the original v8 abliteration pass; the MTP head is independent of that pathway.

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 · AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-BF16 ↗2026/10/30 07:36:34
huggingface · enrich:833941dd-6d5a-412a-b1c6-633b37f06125 ↗2026/10/30 21:05:47

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。