Can Llama 4 Scout 17B 16E run on NVIDIA H200 PCIe 141GB?
YES — Runs Great
Llama 4 Scout 17B 16E needs ~84.7 GB VRAM. NVIDIA H200 PCIe 141GB has 141.0 GB. With Q4_K_M quantization, expect ~154 tok/s.
Operating mode
Choose the run profile you care about
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
154.2 tok/s
TTFT
1256 ms
Safe context
323K
Memory
84.7 GB / 141.0 GB
Memory breakdown
See how fast it feels
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 154.2 tok/s | 685 ms | 323K |
| Coding | A | Runs well | 154.2 tok/s | 1256 ms | 323K |
| Agentic Coding | A | Runs well | 154.2 tok/s | 1826 ms | 323K |
| Reasoning | A | Runs well | 154.2 tok/s | 1484 ms | 323K |
| RAG | A | Runs well | 154.2 tok/s | 2283 ms | 323K |
Quantization options
How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on NVIDIA H200 PCIe 141GB (141.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 42.5 GB | Low | A70 |
Q3_K_S | 3 | 53.4 GB | Low | A72 |
NVFP4 | 4 | 61.0 GB | Medium | A73 |
Q4_K_M | 4 | 66.5 GB | Medium | A74 |
Q5_K_M | 5 | 78.5 GB | High | A76 |
Q6_K | 6 | 89.4 GB | High | A76 |
Q8_0Best for your GPU | 8 | 116.6 GB | Very High | A76 |
F16 | 16 | 223.5 GB | Maximum | F0 |
Get started
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
More models your NVIDIA H200 PCIe 141GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 58.4 tok/s | ||
| 122B | S | 162.1 tok/s | ||
| 119B | S | 175.8 tok/s | ||
| 117B | S | 61.4 tok/s | ||
| 111B | S | 65 tok/s |
Frequently asked questions
Can NVIDIA H200 PCIe 141GB run Llama 4 Scout 17B 16E?
Yes, NVIDIA H200 PCIe 141GB can run Llama 4 Scout 17B 16E with a A grade (Runs well). Expected decode speed: 154.2 tok/s.
How much VRAM does Llama 4 Scout 17B 16E need?
Llama 4 Scout 17B 16E (109B parameters) requires approximately 84.7 GB of memory with Q4_K_M quantization.
What is the best quantization for Llama 4 Scout 17B 16E?
The recommended quantization for Llama 4 Scout 17B 16E is Q4_K_M, which balances quality and memory efficiency.
What speed will Llama 4 Scout 17B 16E run at on NVIDIA H200 PCIe 141GB?
On NVIDIA H200 PCIe 141GB, Llama 4 Scout 17B 16E achieves approximately 154.2 tokens per second decode speed with a time-to-first-token of 1256ms using Q4_K_M quantization.
Can NVIDIA H200 PCIe 141GB run Llama 4 Scout 17B 16E for coding?
For coding workloads, Llama 4 Scout 17B 16E on NVIDIA H200 PCIe 141GB receives a A grade with 154.2 tok/s and 323K context.
What context window can Llama 4 Scout 17B 16E use on NVIDIA H200 PCIe 141GB?
On NVIDIA H200 PCIe 141GB, Llama 4 Scout 17B 16E can safely use up to 323K tokens of context. The model's official context limit is 10.5M, but available memory constrains the safe maximum.
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