Gemma 4 12B
A 12 billion-parameterHow many numbers the model learned during training — the usual rough measure of its size. dense model from Google DeepMind.
- Size
- 12Bdense
- Memory to run
- —smallest, 8K ctx
- Context
- 256Ktokens
- License
- License unknown
- Updated
- 23 May 2026
Where it runs
Best-fitting version on each reference system, at an 8K contextHow much text the model can consider at once, counted in tokens — roughly ¾ of a word each..
Measured throughput
Versions & downloads
Each version is a separate set of weights. Expand one for its downloads: quantizationStoring each of the model’s numbers with fewer bits, so the file is smaller and needs less memory. trades a little quality for a much smaller file, and the memory column adds the working memoryExtra space the model needs while it answers. It grows with the length of the conversation, on top of the file itself. a conversation needs on top.
Benchmarks
Each benchmarkA fixed set of questions every model is given, so their scores can be compared on the same task. score is labelled with who produced it. Developer-reported scores use each lab’s own prompts and settings; a benchmark that runs every model itself uses one setup for all. Bars are relative to the best open result.
Community
Benchmark runs and reviews from people running it on their own hardware.
Benchmark runs
Reviews
Details & sources
Architecture
- Parameters
- 11.96B
- Active / token
- All (dense)
- Architecture
- Dense
- Layers
- 48
- Attention heads
- 16
- KV heads
- 8
- Head dim
- 256
- KV cache @ 8K (fp16)
- 3.00 GiB
- Max context
- 262,144 tokens
Lineage
How this model’s versions relate to each other and to other models.
Sources
No source records linked.
Timeline
- Gemma 4 released