Gemma 4 12B
consumerSmartest model in the 8-16GB class. Competes with models 2x larger. Gemma 4 generation with MTP support.
AI-generated content marks
The provider reports that this model does not add embedded watermarks or provenance metadata to generated output.
- 12.0B
- 128k
- other
- 🇺🇸 USA
- Jun 2025
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Per-quant memory needs and a static "can you run it?" reference - no rig entry required
The reference hardware
22 reference configs, drawn in-house. Scroll for more.
Can you run it? - reference rigs
| Rig | Q4_K_M | Q8_0 |
|---|---|---|
| 4x H100 80GB (320GB) | fast 814.9t/s | fast 496.5t/s |
| NVIDIA DGX Station 748GB | fast 486.5t/s | fast 296.4t/s |
| 8x RTX 3090 rack (192GB) | fast 455.5t/s | fast 277.5t/s |
| 4x RTX 5090 (128GB) | fast 435.9t/s | fast 265.6t/s |
| AMD Instinct MI300X (192GB) | fast 323.8t/s | fast 197.3t/s |
| 4x RTX 4090 (96GB) | fast 245.2t/s | fast 149.4t/s |
| 2x RTX 5090 (64GB) | fast 218.0t/s | fast 132.8t/s |
| 2x RTX 3090 (48GB) | fast 113.9t/s | fast 69.4t/s |
| Single RTX 5090 (32GB) | fast 109.0t/s | fast 66.4t/s |
| RTX PRO 6000 Blackwell (96GB) | fast 109.0t/s | fast 66.4t/s |
| Mac Studio M4 Ultra 192GB | fast 72.5t/s | fast 44.1t/s |
| Mac Studio M4 Ultra 512GB | fast 72.5t/s | fast 44.1t/s |
| Single RTX 4090 (24GB) | fast 61.3t/s | fast 37.4t/s |
| MacBook Pro M5 Max 128GB | fast 40.7t/s | fast 24.8t/s |
| Single GTX 1080 Ti (11GB) | fast 29.4t/s | offload |
| Dual EPYC 9004 + 768GB DDR5-4800 | fast 28.0t/s | ok 17.1t/s |
| DGX Spark 128GB unified | ok 16.6t/s | ok 10.1t/s |
| Ryzen AI Max+ 395 128GB | ok 15.6t/s | ok 9.5t/s |
| Jetson AGX Orin 64GB | ok 12.5t/s | slow 7.6t/s |
| Epyc + 512GB DDR4-3200 + 2x RTX 3090 | ok 12.5t/s | slow 7.6t/s |
| Epyc + 512GB DDR4-2400 + 2x RTX 3090 | ok 9.3t/s | slow 5.7t/s |
| NVIDIA Jetson Orin NX 16GB | slow 6.2t/s | slow 3.8t/s |
Fit tiers use the same will-it-run logic as the rig finder. For comfortable fits, the badge reflects decode speed: fast >=20 t/s, ok 8-20 t/s, slow <8 t/s. t/s is a bandwidth estimate, not a measured benchmark.
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Inference cost over time
Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.
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