Model overview
An imatrix-calibrated, **Unsloth-Dynamic-style** GGUF ladder for **Ornith-1.5-35B-A3B** — the model's own weights and chat template, re-quantized with a per-tensor precision policy and a fresh importance matrix. **The MTP (`nextn`) block is removed from every tier** — Ornith-1.5 ships it untrained, so it could only add size. Why. > ### Not affiliated with Unsloth > This is an independent, best-effort community reproduction of Unsloth's > Dynamic GGUF method — **not** an > official Unsloth release, and not endorsed by or connected to Unsloth in any way. Unsloth had not > published their own Ornith-1.5 quants at the time of writing and a lot of people wanted them, so > we published these while we wait. If and when Unsloth ship an official build, use theirs. "Unsloth" > is used here only to name the *method* these quants reproduce. 1. **Unsloth-Dynamic per-tensor policy.** Instead of one bit-width for the whole model, each tensor gets a type chosen by sensitivity — more bits where they matter (embeddings, attention, early/late layers), fewer where they don't. We transfer the published per-tensor recipe from Unsloth's `Qwen3.6-35B-A3B-GGUF` (same `qwen35moe` architecture) tier-for-tier. 2. **A fresh importance matrix.** Computed on Ornith's own `BF16` over an interleaved multilingual + code calibration corpus, so the quantizer knows which weights to protect for *this* model rather than inheriting someone else's statistics.
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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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。