Versus Engine
Gemma 3 (27B) vs Llama 3.3 (70B)
Specs, price and the one trade-off that actually decides it — Gemma 3 (27B) against Llama 3.3 (70B), 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
Llama 3.3 (70B)
The open-weights reference point at 70B — the strongest local option if the hardware exists.
Where it wins, where it doesn't
Pros
- The reference standard for open-weights models
- Competitive with frontier closed models on practical tasks
- Unmatched fine-tuning and serving ecosystem
Cons
- Needs roughly 64GB of VRAM or unified memory to run well
- Heavy energy cost under sustained inference
- Aggressive quantisation costs the quality you bought it for