PulseAugur
EN
LIVE 21:23:03

New inference engine boosts Qwen 3.6-35B-A3B performance on 16GB GPUs

A new inference engine called AgrillaMoE has been developed, forking from llama.cpp to optimize the Qwen 3.6-35B-A3B model for use on a 16GB GPU. This engine utilizes Unsloth quants and a novel "MoE expansion" technique that allows more of the model's experts to be consulted per token without retraining. This method reportedly improves performance on benchmarks like GPQA-Diamond, achieving a higher score than the stock configuration. AI

IMPACT Enables more efficient use of large language models on consumer-grade hardware, potentially lowering the barrier to entry for advanced AI applications.

RANK_REASON This is a user-developed tool/engine for optimizing an existing model, not a release from a frontier lab or a significant industry event.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New inference engine boosts Qwen 3.6-35B-A3B performance on 16GB GPUs

How we ranked this

Signal score
5 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
This is a user-developed tool/engine for optimizing an existing model, not a release from a frontier lab or a significant industry event.
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
infra, model release
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Specific-Tax-6700 ·

    poorman inference engine for 16GB GPU and 35B moe Qwen 3.6for coding

    <!-- SC_OFF --><div class="md"><p>I forked llama.cpp's server into AgrillaMoE, a dedicated build for Qwen3.6-35B-A3B (~A4B) with Unsloth quants. On a (vant.ai) rented V100 16GB with the 2-bit UD-Q2_K_XL quant it generates at ~57-60 tok/s while running the full MoE-expansion profi…