REDDIT · REDDIT// 7d agoTUTORIAL

Gemma 4 26B-A4B Fits 16 GB VRAM

This Reddit post argues that Gemma 4 26B A4B, especially the Unsloth IQ4_XS GGUF quant, is the strongest option for running Gemma 4 on a 16 GB GPU if you want to keep multimodal vision. The author claims that low-temperature sampling, conservative top-k/top-p settings, and a minimum image token budget materially improve coding and vision quality, while FP16 mmproj and a large fp16 KV cache still fit within the memory budget.

// ANALYSIS

Hot take: for users who care about local multimodal performance on constrained hardware, this reads less like a benchmark flex and more like a practical deployment recipe.

–The post is a configuration guide first and a benchmark comparison second, so `tutorial` fits better than a pure benchmark category.
–The core recommendation is the `unsloth/gemma-4-26B-A4B-it-GGUF` IQ4_XS quant, with `mmproj-F16.gguf` and tuned decoding parameters.
–The main claim is that this setup balances quality, speed, and VRAM usage better than other quantizations the author tested, including Bartowski variants.
–The vision advice is specific and actionable: keep `--image-min-tokens 300` and avoid wasting memory on higher-precision mmproj or KV quantization if it hurts quality.
–The comparison against Qwen 3.5 27B is useful context, but it is still anecdotal and should be treated as a single-user field report rather than a controlled benchmark.

// TAGS

gemma-4-26b-a4bunslothggufllama-cppmoemultimodalvisionquantizationlocal-llm16gb-vramcoding

DISCOVERED

7d ago

2026-04-05

PUBLISHED

7d ago

2026-04-05

RELEVANCE

9/ 10

AUTHOR

Sadman782