Model overview
A 27B dense vision-language model (27.8B including the vision tower). 64 decoder layers in a hybrid stack: `full_attention_interval=4` means every fourth layer is grouped-query full attention (16 layers) and the rest are Gated DeltaNet linear attention (48 layers). Vocab 248320 with untied embeddings. Context length 262144 natively, extensible further with YaRN. The mmproj file is separate by design: llama.cpp loads the text backbone and the vision projector as two files. Download one tier plus one mmproj. Without the mmproj the model still runs, but text-only. The `mmproj-` and `mtp-` prefixes are what recent llama.cpp builds match on to tell the three file kinds apart, so `-hf 6block/Qwen3.8-27B-GGUF` picks a backbone rather than a projector, and `--spec-type mtp` finds the draft on its own.
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?
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Are these real-time billing prices?
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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。