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EryriLabs
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Model Details
Model Provider
EryriLabs
Model Tree
endless-frontier/BigBang-v1
Qwen/Qwen3.6-35B-A3B
ornith-ai/Ornith-1.5-35B-A3B
Input Modalities
Output Modalities
Supported Functionality
Ornith-1.5-35B-A3B ships 785 mtp.* tensors that are random initialisation, not trained weights: every projection has
std = 0.0200 with Gaussian kurtosis 3.0 (i.e. exactly initializer_range=0.02), and its norm weights sit near 0.02 instead
of ~1. Used as a speculative draft it accepts only ~13% of tokens (pure chance). This model replaces that placeholder with
the trained MTP head from Qwen3.6-35B-A3B, which transfers cleanly because Ornith's language tower is only ~0.2–1%
away from Qwen3.6 (measured cosine per tensor group).
Measured with llama.cpp speculative decoding (Q4_K_M main + Q8_0 draft, RTX 3090):
| draft head | acceptance | mean accepted run |
|---|---|---|
| Qwen3.6 grafted (this model) | 0.55–0.75 (code high, chat lower) | 3.2–4.0 tokens |
| Ornith-1.5 stock (random init) | ~0.13 | ~1.5 |
mtp.*: Qwen3.6's trained head, verbatim (fused-expert layout, loads with the same Qwen3_5MoeForConditionalGeneration class).| this merge | stock Ornith-1.5 | |
|---|---|---|
| 15-task Python pass@1 | 15/15 | 15/15 |
| perplexity (mixed code+prose) | 3.34 | 3.41 |
| generation speed (no draft) | 131.0 tok/s | 133.9 tok/s |
| speed with MTP draft | 169.4 tok/s (+29%) | n/a (head is untrained) |
Chat, instruction-following, translation and creative prompts remain coherent (spot-checked; e.g. Welsh translation is understandable but slightly unnatural). This is a small local eval, not a benchmark suite — treat it as a no-regression check plus the MTP head-to-head, not a leaderboard claim.
<think>), inherited from Ornith/Qwen3.6. Give generous max_tokens.Merged and measured by EryriLabs (Dwain Barnes), 2026-08-20.