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DiffusionGemma 26B A4B tuned for RTX 5090, boosting speed

By PulseAugur Editorial · [1 sources] ·

A user on Reddit shared their tuning results for the DiffusionGemma 26B A4B model, specifically focusing on performance with a RTX 5090 GPU. They detailed optimal parameters and provided speed comparisons for different quantization levels and context lengths. The tuning significantly improved throughput, with the Q4_K_M variant showing up to a 44% speedup for longer contexts. AI

IMPACT Demonstrates how parameter tuning can significantly enhance the performance of open-source models on consumer hardware.

RANK_REASON User-generated tuning results and performance benchmarks for an open-source model. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

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

DiffusionGemma 26B A4B tuned for RTX 5090, boosting speed

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0 / 100
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Tool
User-generated tuning results and performance benchmarks for an open-source model. [lever_c_demoted from research: ic=1 ai=1.0]
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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.
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model release, product
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High
Clearly on-topic for AI-industry coverage.
Story freshness
107 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/giveen ·

    DiffusionGemma 26B A4B results on my 5090

    <!-- SC_OFF --><div class="md"><p># DiffusionGemma 26B A4B — Tuning Results </p> <p><a href="https://huggingface.co/unsloth/diffusiongemma-26B-A4B-it-GGUF">https://huggingface.co/unsloth/diffusiongemma-26B-A4B-it-GGUF</a></p> <p>## System</p> <p>- **GPU**: RTX 5090 (32 GB VRAM), …

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