---

license: mit

base_model:

- deepreinforce-ai/Ornith-1.0-35B

base_model_relation: quantized

language:

- en

library_name: gguf

tags:

- gguf

- llama.cpp

- mtp

- multi-token-prediction

- speculative-decoding

- qwen35moe

- moe

pipeline_tag: text-generation

---

Ornith-1.0-35B-MTP-GGUF

Ornith-1.0-35B (qwen35moe, 35B-A3B,

Qwen3.5 base) is a strong agentic-coding MoE that ships without MTP heads. This GGUF has an

MTP head grafted in so it can use llama.cpp's --spec-type draft-mtp self-speculative

decoding for a real speedup, with no quality change to the base weights.

Quantization: Q6_K (body + grafted MTP head).

Performance (M3 Max, measured, real-prompt benchmark)

Generation speed (tg128) on a real code-continuation prompt, sweeping draft depth:

| Mode | tok/s | Speedup | MTP acceptance | mean accepted len |

|---|---|---|---|---|

| AR (no MTP) | 66.6 | 1.00× | — | — |

| draft-mtp n_max=1 | 83.8 | 1.26× | 92.2% | 1.92 |

| draft-mtp n_max=2 | 82.8 | 1.24× | 82.5% | 2.65 |

| draft-mtp n_max=3 | 81.7 | 1.23× | 78.2% | 3.35 |

| draft-mtp n_max=4 | 75.9 | 1.14× | 68.1% | 3.72 |

Best: --spec-draft-n-max 1, ~1.26×. (Acceptance is much higher on real text than on random

tokens — benchmark with a real prompt or you'll badly underestimate MTP.)

Usage (llama.cpp)

llama-server -m Ornith-1.0-35B-Q6_K-MTP.gguf -ngl 99 -c 32768 \
  --spec-type draft-mtp --spec-draft-n-max 1 --port 8080

Requires a llama.cpp build with draft-mtp speculative support.

Provenance & licensing

• Base model: deepreinforce-ai/Ornith-1.0-35B — MIT.
• MTP head: grafted from a same-architecture (qwen35moe, 40 blocks) sibling that ships MTP

heads, following the cross-model graft approach published by

skinnyctax/Ornith-1.0-35B-Q6_K-Frankenstein-MTP-GGUF (MIT).

The 20 MTP head tensors (blk.40., incl. nextn.) are appended to the base GGUF and metadata

patched (block_count +1, nextn_predict_layers=1).

Released under MIT. No weights retrained — this is a head graft + metadata patch.