Versus Engine
Gemma 3 (27B) vs Qwen 3 MoE
Specs, price and the one trade-off that actually decides it — Gemma 3 (27B) against Qwen 3 MoE, side by side.
Cheaper to start
Tie
Both start at a similar price.
Best ecosystem
Tie
Neither lists native integrations.
Standout
Gemma 3 (27B)
Fits comfortably in 32GB of unified memory
Gemma 3 (27B)
Google's 27B open-weights model, tuned to fit machines with 32GB of unified memory.
Where it wins, where it doesn't
Pros
- Fits comfortably in 32GB of unified memory
- Matches or beats the previous generation of 70B models
- Native multimodal capability at this size
Cons
- Google's licence carries commercial restrictions worth legal review
- Still needs mid-tier hardware at minimum
- Weaker fine-tuning ecosystem than Llama
Qwen 3 MoE
A large Mixture-of-Experts model offering frontier-class performance outside the US provider ecosystem.
Where it wins, where it doesn't
Pros
- Frontier-class performance from outside the US provider ecosystem
- MoE architecture keeps inference fast for the parameter count
- Open weights with permissive access
Cons
- Memory footprint is the full parameter count despite sparse activation
- Enterprise procurement often raises provenance objections
- Local deployment harder than the effective size implies