Llama 4 Scout 17B 16E needs ~89.4 GB VRAM. H100 NVL 188GB has 188.0 GB. With Q4_K_M quantization, expect ~242 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
241.6 tok/s
TTFT
801 ms
Safe context
554K
Memory
89.4 GB / 188.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 241.6 tok/s | 437 ms | 554K |
| Coding | A | Runs well | 241.6 tok/s | 801 ms | 554K |
| Agentic Coding | A | Runs well | 241.6 tok/s | 1166 ms | 554K |
| Reasoning | A | Runs well | 241.6 tok/s | 947 ms | 554K |
| RAG | A | Runs well | 241.6 tok/s | 1457 ms | 554K |
How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on H100 NVL 188GB (188.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 42.5 GB | Low | B68 |
Q3_K_S | 3 | 53.4 GB | Low | B70 |
NVFP4 | 4 | 61.0 GB | Medium | A71 |
Q4_K_M | 4 | 66.5 GB | Medium | A71 |
Q5_K_M | 5 | 78.5 GB | High | A73 |
Q6_K | 6 | 89.4 GB | High | A74 |
Q8_0Best for your GPU | 8 | 116.6 GB | Very High | A76 |
F16 | 16 | 223.5 GB | Maximum | F0 |
Copy-paste commands to run Llama 4 Scout 17B 16E on your machine.
Run
lms load Llama-4-Scout-17B-16E-Instruct && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 91.6 tok/s | ||
| 122B | S | 254 tok/s | ||
| 284B | S | 136.1 tok/s | ||
| 119B | S | 275.4 tok/s | ||
| 117B | S | 96.3 tok/s |
Yes, H100 NVL 188GB can run Llama 4 Scout 17B 16E with a A grade (Runs well). Expected decode speed: 241.6 tok/s.
Llama 4 Scout 17B 16E (109B parameters) requires approximately 89.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Llama 4 Scout 17B 16E is Q4_K_M, which balances quality and memory efficiency.
On H100 NVL 188GB, Llama 4 Scout 17B 16E achieves approximately 241.6 tokens per second decode speed with a time-to-first-token of 801ms using Q4_K_M quantization.
For coding workloads, Llama 4 Scout 17B 16E on H100 NVL 188GB receives a A grade with 241.6 tok/s and 554K context.
On H100 NVL 188GB, Llama 4 Scout 17B 16E can safely use up to 554K tokens of context. The model's official context limit is 10.5M, but available memory constrains the safe maximum.
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<iframe src="https://willitrunai.com/embed/llama-4-scout-17b-16e-on-h100-nvl-188gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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