Raises estimated decode speed by about 488%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
Llama 3.2 11B Vision needs ~38.8 GB VRAM. NVIDIA DGX Spark 128GB has 0 MB. With F16 quantization, expect ~11 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
26.2 tok/s
TTFT
7377 ms
Safe context
16K
Memory
22.9 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 | B | Runs well | 26.2 tok/s | 4024 ms | 16K |
| Coding | F | Too heavy | 4.4 tok/s | 44060 ms | 4K |
| Agentic Coding | B | Runs well | 26.2 tok/s | 10731 ms | 16K |
| Reasoning | B | Runs well | 26.2 tok/s | 8719 ms | 16K |
| RAG | B | Runs well | 26.2 tok/s | 13414 ms | 16K |
How Llama 3.2 11B Vision (11B params) fits at each quantization level on NVIDIA DGX Spark 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.3 GB | Low | C54 |
Q3_K_S | 3 | 5.4 GB | Low | C54 |
NVFP4 | 4 |
Copy-paste commands to run Llama 3.2 11B Vision on your machine.
Run
ollama run llama3.2-vision:11bUpgrade options
Raises estimated decode speed by about 488%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
Raises estimated decode speed by about 488%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
Raises estimated decode speed by about 488%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
Yes, NVIDIA DGX Spark 128GB can run Llama 3.2 11B Vision at F16 quantization (Runs well). The recommended Q4_K_M requires 9.9 GB which exceeds available memory, but at F16 it needs only 38.8 GB. Expected decode speed: 10.9 tok/s.
Llama 3.2 11B Vision (11B parameters) requires approximately 9.9 GB at Q4_K_M quantization. On NVIDIA DGX Spark 128GB, it fits at F16 using 38.8 GB.
The recommended quantization is Q4_K_M, but on NVIDIA DGX Spark 128GB the best fitting quantization is F16, which uses 38.8 GB.
On NVIDIA DGX Spark 128GB, Llama 3.2 11B Vision achieves approximately 10.9 tokens per second decode speed with a time-to-first-token of 17709ms using F16 quantization.
For coding workloads, Llama 3.2 11B Vision on NVIDIA DGX Spark 128GB receives a F grade with 4.4 tok/s and 4K context.
On NVIDIA DGX Spark 128GB, Llama 3.2 11B Vision can safely use up to 16K tokens of context at F16 quantization. The model's official context limit is 16K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/llama-3.2-11b-vision-on-dgx-spark-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
6.2 GB |
| Medium |
| C54 |
Q4_K_M | 4 | 6.7 GB | Medium | C54 |
Q5_K_M | 5 | 7.9 GB | High | C54 |
Q6_K | 6 | 9.0 GB | High | C54 |
Q8_0 | 8 | 11.8 GB | Very High | C54 |
F16Best for your GPU | 16 | 22.5 GB | Maximum | B55 |
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.