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)

bash

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.

wang-yang/Ornith-1.0-35B-MTP-GGUF

Ornith-1.0-35B-MTP-GGUF

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

Usage (llama.cpp)

Provenance & licensing

wang-yang/
Ornith-1.0-35B-MTP-GGUF