Ornith-1.5-35B-A3B-GGUF

Model overview

GGUF quantizations of ornith-ai/Ornith-1.5-35B-A3B, made with an importance matrix, plus a KL-divergence comparison with the other published GGUFs of this model. > [!NOTE] > These files were made for a quantization experiment and are evaluated only by the KLD measurements below, not by task benchmarks, long-context use or speed tests. Check them on your own workload before relying on them. The four "comparison only" files are there so that the effect of `-hq` in the tables below can be checked; at each size the `-hq` file is better. All files are Q4_K_M with up to two kinds of changes. The `-hq` part raises the tensors outside the routed experts to Q8_0: attention, the linear-attention (SSM) projections, the shared expert, and the MTP projection. The `-exps` part changes the routed expert tensors (`ffn_{gate,up,down}_exps`) in layers 0-39. The token embedding and the output keep the Q4_K_M types (Q4_K and Q6_K). All files keep the built-in MTP (NextN) layer, so they work with `--spec-type draft-mtp`. For image input, use the vision projector from the official repo (`mmproj-Ornith-1.5-35B-BF16.gguf`).

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.

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。

Frequently asked questions

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。