llamaperf

Ornith1.5 35B (3B active) BigBang

on NVIDIA RTX 3090 · llama.cpp

Tone: positiveNVIDIA hardware
Oct 4, 2026
Throughput
169.4 t/s gen
Quant
Q4_K_M (GGUF)

Use cases

codingagentic

Summary

User reports Ornith-1.5-35B-A3B-BigBang-MTP at 169.4 tok/s with MTP speculative decoding on a single RTX 3090, up 29% from 131.0 tok/s without the draft. Setup is llama.cpp with Q4_K_M main weights and a Q8_0 draft, single RTX 3090, temp 0.1. The grafted Qwen3.6 MTP head accepts 0.55-0.75 of tokens (code high, chat lower) with mean accepted runs of 3.2-4.0 tokens, versus ~0.13 acceptance for stock Ornith-1.5's random-init head. Stock Ornith-1.5 measured 133.9 tok/s without a draft. Perplexity on mixed code and prose was 3.34 versus 3.41 for stock, and both scored 15/15 on a 15-task Python pass@1. The author calls this a small local eval, not a benchmark suite.