Open Source

Qwen3.5-9B beats Google's Gemma-4-12b-it in 5 of 8 benchmarks despite smaller size

A 9B-parameter model outperforms a 12B rival across most shared tests, challenging the hype around Google's latest.

Deep Dive

According to official HuggingFace model cards, Qwen outperforms Gemma for its size and has a lighter KV cache. Gemma-4-12b-it might be a slightly better coder than Qwen3.5-9b, but a Qwen finetune (Omnicoder-9B) offers a competitive alternative. The results highlight Qwen's efficiency advantage.

Key Points
  • Qwen3.5-9B wins 5/8 shared benchmarks against Gemma-4-12b-it on HuggingFace model card data, despite being 25% smaller (9B vs 12B).
  • Gemma-4-12b-it only beats Qwen in coding tasks, but a Qwen finetune (Omnicoder-9B) rivals it, narrowing that lead.
  • Qwen also features a lighter KV cache, meaning lower memory and latency during inference—critical for edge deployment.

Why It Matters

Model size isn't everything: smaller, well-tuned open models can outperform larger rivals, cutting costs and democratizing AI.