gemma 3 12b it needs ~23.0 GB VRAM. NVIDIA DGX Spark 128GB has 108.8 GB. With Q4_K_M quantization, expect ~22 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
22.4 tok/s
TTFT
8652 ms
Safe context
992K
Memory
23.0 GB / 108.8 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 22.4 tok/s | 4719 ms | 992K |
| Coding | C | Runs well | 22.4 tok/s | 8652 ms | 992K |
| Agentic Coding | C | Runs well | 22.4 tok/s | 12584 ms | 992K |
| Reasoning | C | Runs well | 22.4 tok/s | 10225 ms | 992K |
| RAG | C | Runs well | 22.4 tok/s | 15730 ms | 992K |
How gemma 3 12b it (12B params) fits at each quantization level on NVIDIA DGX Spark 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.7 GB | Low | D39 |
Q3_K_S | 3 | 5.9 GB | Low | D39 |
NVFP4 | 4 | 6.7 GB | Medium | D39 |
Q4_K_M | 4 | 7.3 GB | Medium | D39 |
Q5_K_M | 5 | 8.6 GB | High | D40 |
Q6_K | 6 | 9.8 GB | High | D40 |
Q8_0 | 8 | 12.8 GB | Very High | D40 |
F16Best for your GPU | 16 | 24.6 GB | Maximum | C42 |
Copy-paste commands to run gemma 3 12b it on your machine.
Run
lms load hf-maziyarpanahi--gemma-3-12b-it-gguf && lms server startOpciones de mejora
NVIDIA H200 141GBOpción económicaSube la velocidad estimada de decodificación alrededor de un 650%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$30,000 MSRP
NVIDIA H200 PCIe 141GBMejor relación calidad-precioSube la velocidad estimada de decodificación alrededor de un 650%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$30,000 MSRP
NVIDIA B200 180GBMejora NVIDIASube la velocidad estimada de decodificación alrededor de un 650%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$30,000 MSRP
Yes, NVIDIA DGX Spark 128GB can run gemma 3 12b it with a C grade (Runs well). Expected decode speed: 22.4 tok/s.
gemma 3 12b it (12B parameters) requires approximately 23.0 GB of memory with Q4_K_M quantization.
The recommended quantization for gemma 3 12b it is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA DGX Spark 128GB, gemma 3 12b it achieves approximately 22.4 tokens per second decode speed with a time-to-first-token of 8652ms using Q4_K_M quantization.
For coding workloads, gemma 3 12b it on NVIDIA DGX Spark 128GB receives a C grade with 22.4 tok/s and 992K context.
On NVIDIA DGX Spark 128GB, gemma 3 12b it can safely use up to 992K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. NVIDIA DGX Spark 128GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.
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