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Qwen3.5-4B tops Gemma 4 E4B in RAG benchmarks

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Qwen3.5-4B tops Gemma 4 E4B in RAG benchmarks
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// 47d agoBENCHMARK RESULT

Qwen3.5-4B tops Gemma 4 E4B in RAG benchmarks

ANNOUNCEMENTPRODUCTPRODUCT HUNT

Reddit and benchmark data confirm Qwen3.5-4B outperforms Gemma 4 E4B in structured RAG, document extraction, and long-context stability. The model is a clear winner for edge-deployed retrieval-augmented generation.

// ANALYSIS

Qwen 3.5 4B is the clear favorite for RAG pipelines, while Gemma 4 E4B leads in raw visual grounding and Android-native multimodal tasks.

  • –Qwen 3.5 4B dominates structured document extraction (OlmOCR 75.4 vs 47.0) and maintains layout integrity far better than Gemma.
  • –Native context support is superior on Qwen with 262K native tokens, ensuring stability in complex RAG workflows.
  • –Both models are rock-solid at 4-bit AWQ, fitting easily into consumer GPUs with ~8GB VRAM for edge inference.
  • –Gemma 4 E4B remains the niche choice for handwriting recognition and raw OCR-as-a-pre-processor tasks.
// TAGS
qwen3.5-4bgemma-4-e4bragllmbenchmarkopen-source

DISCOVERED

47d ago

2026-04-10

PUBLISHED

47d ago

2026-04-10

RELEVANCE

8/ 10

AUTHOR

blackkksparx