Gemma 4 12B
Unified text, image, and audio understanding in a compact Gemma 4 model.
- Published size
- 11.95B
- Active parameters
- 11.95B
- Context window
- 256K
- Architecture
- Dense · multimodal
- License
- Apache 2.0
Deployment considerations
The unified architecture processes multiple modalities without separate encoders. Test text, image, and audio workloads individually.
The model card lists 11.95B parameters and a 256K context window for the instruction-tuned 12B Unified model.
GPU memory estimates and minimum / recommended configurations are pending. This profile does not contain measured deployment results.
GPU requirements
- Minimum
- —GPU / VRAM · pending
- Recommended
- —GPU / VRAM · pending
Memory estimates and tested configurations will appear here after checkpoint review and deployment testing.
No invented leaderboards.
Latency, throughput, and cost per token will appear here after a reproducible run. Until then, this page helps you understand the model—not predict its performance.
Gemma 4 12B deployment FAQ
How much GPU memory does Gemma 4 12B need?
The full checkpoint weight footprint is pending review. Minimum and recommended GPU configurations will be added after testing; the model name or active parameter count alone is not a memory requirement.
Has BenchGrid benchmarked Gemma 4 12B?
Not yet. This profile contains publisher specifications and calculated weight-memory estimates. We do not currently publish measured latency, throughput, or cost per token for this model.
Where do these specifications come from?
The specifications are based on the official Google model card linked on this page. Memory estimates use the stated total parameter count, including inactive experts for MoE models. Nominal model sizes are labeled with ~.
Explore your compute options.
Check available hardware, quotas, and current pricing with the provider. These links are not verified deployments or performance recommendations.
