stablelm 2 zephyr 1 6b needs ~18.6 GB VRAM. NVIDIA DGX Spark 128GB has 108.8 GB. With Q4_K_M quantization, expect ~45 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
44.8 tok/s
TTFT
4326 ms
Safe context
2.1M
Memory
18.6 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 | F | Too heavy | 8.1 tok/s | 13109 ms | 4K |
| Coding | C | Runs well | 44.8 tok/s | 4326 ms | 2.1M |
| Agentic Coding | C | Runs well | 44.8 tok/s | 6292 ms | 2.1M |
| Reasoning | C | Runs well | 44.8 tok/s | 5112 ms | 2.1M |
| RAG | C | Runs well | 44.8 tok/s | 7865 ms | 2.1M |
How stablelm 2 zephyr 1 6b (6B params) fits at each quantization level on NVIDIA DGX Spark 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.3 GB | Low | D39 |
Q3_K_S | 3 | 2.9 GB | Low | D39 |
NVFP4 | 4 | 3.4 GB | Medium | D39 |
Q4_K_M | 4 | 3.7 GB | Medium | D39 |
Q5_K_M | 5 | 4.3 GB | High | D39 |
Q6_K | 6 | 4.9 GB | High | D39 |
Q8_0 | 8 | 6.4 GB | Very High | D39 |
F16Best for your GPU | 16 | 12.3 GB | Maximum | D40 |
Copy-paste commands to run stablelm 2 zephyr 1 6b on your machine.
Run
lms load hf-stabilityai--stablelm-2-zephyr-1-6b && lms server startUpgrade-Optionen
NVIDIA H200 141GBGünstige WahlRaises estimated decode speed by about 88%.
Adds memory headroom for longer context windows and future model growth.
ca. $30,000 MSRP
NVIDIA H200 PCIe 141GBBestes Preis-Leistungs-VerhältnisRaises estimated decode speed by about 88%.
Adds memory headroom for longer context windows and future model growth.
ca. $30,000 MSRP
NVIDIA B200 180GBNVIDIA-UpgradeRaises estimated decode speed by about 88%.
Adds memory headroom for longer context windows and future model growth.
ca. $30,000 MSRP
Yes, NVIDIA DGX Spark 128GB can run stablelm 2 zephyr 1 6b with a C grade (Runs well). Expected decode speed: 44.8 tok/s.
stablelm 2 zephyr 1 6b (6B parameters) requires approximately 18.6 GB of memory with Q4_K_M quantization.
The recommended quantization for stablelm 2 zephyr 1 6b is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA DGX Spark 128GB, stablelm 2 zephyr 1 6b achieves approximately 44.8 tokens per second decode speed with a time-to-first-token of 4326ms using Q4_K_M quantization.
For coding workloads, stablelm 2 zephyr 1 6b on NVIDIA DGX Spark 128GB receives a C grade with 44.8 tok/s and 2.1M context.
On NVIDIA DGX Spark 128GB, stablelm 2 zephyr 1 6b can safely use up to 2.1M 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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