Versus Engine
Gemma 3 (27B) vs Llama 3.3 (70B)
Recorded capabilities and trade-offs for Gemma 3 (27B) and Llama 3.3 (70B), side by side. Missing information is not treated as a tie.
Capabilities on record
Gemma 3 (27B)
No structured feature record is available.
Capabilities on record
Llama 3.3 (70B)
No structured feature record is available.
Gemma 3 (27B)
Google's 27B open-weights model, tuned to fit machines with 32GB of unified memory.
Editorial notes on record
Recorded strengths
- Fits comfortably in 32GB of unified memory
- Matches or beats the previous generation of 70B models
- Native multimodal capability at this size
Recorded limitations
- 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.
Editorial notes on record
Recorded strengths
- The reference standard for open-weights models
- Competitive with frontier closed models on practical tasks
- Broad fine-tuning and serving ecosystem
Recorded limitations
- 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