Model overview
A **family of nine GGUF files** of `Qwen3.8-27B` (the native vision-language 27B dense model, Gated DeltaNet + Gated Attention hybrid layout, 262,144-token native context, MTP speculative head), converted from unsloth/Qwen3.8-27B-NVFP4. The **MTP (multi-token prediction) speculative head is baked into every file** — no separate drafter needed. - **`ORIG`** — the source-preserving conversion: native **NVFP4 MLP backbone** + **BF16 attention/embeddings** (the source's F8 attention is dequantized to BF16 because GGML has no F8 tensor type). This is the largest file and the one all tiers are derived from. - **`VERY-LOW` / `COMPACT-LOW` / `LOW` / `MEDIUM` / `MID-HIGH` / `HIGH` / `VERY-HIGH`** — a compact family sharing a **byte-identical 448-tensor NVFP4 backbone** (all attention + MLP re-quantized to NVFP4), differing only in the 10 "extra" tensors (LM head, token embedding, MTP draft head). `COMPACT-LOW` fills the gap between `VERY-LOW` and `LOW` — slightly smaller than `LOW` while keeping a materially stronger LM head than `VERY-LOW` (Q4_K vs Q3_K). `MID-HIGH` sits between `MEDIUM` and `HIGH` with all three head groups at **Q8_0**. - **`HIGHEST`** — the top tier: keeps the source's native **NVFP4 MLP** (layers 0-55) exactly as in `ORIG`, restores **Q8_0** for attention + the late MLP layers + the LM head, and keeps the **token embedding + MTP head in BF16**. The closest compact approximation of the source layout, for high-end GPUs. The goal: **keep native NVFP4 density across the whole model for Blackwell**, and offer a size/precision ladder for the tensors that most affect output quality and decode speed. On our dual 16 GB Blackwell setup every tier fits and runs (see notes before treating any numbers as meaningful).
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：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。