llamaperf

Nemotron 3.5 74B (9B active) Bolt

on NVIDIA RTX 3090 · llama.cpp · 16,384 ctx

Tone: mixedNVIDIA hardware
Oct 16, 2026
Throughput
85.2 t/s gen · 833.0 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
IQ2_XXS (GGUF)
KV cache
q8_0

Use cases

codingtool-useagentic

Summary

User benchmarks Nemotron 3.5 Bolt 74B-A9B at 85.2 tok/s decode and 833 tok/s prompt on an RTX 3090, against Qwen3.8 27B Q4_K_M at 41.5 tok/s decode and 963 tok/s prompt. Setup is llama.cpp with IQ2_XXS GGUF weights, q8_0 KV cache, 16K context, all 89 layers on GPU with no CPU offload, 21.3GB peak VRAM. No speculative decoding. On a 5090 the same models ran at 148.3 vs 72.5 tok/s decode. Qwen passed more tasks on both cards (89/120 vs 75/120 on 3090, 84/120 vs 71/120 on 5090); the gap was almost entirely tool calling, where Nemotron had 20 truncations at a 512-token per-turn cap. Median time-to-finished-task was a tie because Nemotron writes about 1.5x more tokens per task.