Can Falcon 40B Instruct run on NVIDIA GH200 96GB?
YES — Runs Great
Falcon 40B Instruct needs ~41.4 GB VRAM. NVIDIA GH200 96GB has 96.0 GB. With Q5_K_M quantization, expect ~115 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
124.8 tok/s
TTFT
1551 ms
Safe context
8K
Memory
41.4 GB / 96.0 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 | 124.8 tok/s | 846 ms | 8K |
| Coding | A | Runs well | 114.8 tok/s | 1687 ms | 8K |
| Agentic Coding | A | Runs well | 124.8 tok/s | 2257 ms | 8K |
| Reasoning | A | Runs well | 124.8 tok/s | 1833 ms | 8K |
| RAG | A | Runs well | 124.8 tok/s | 2821 ms | 8K |
Quantization options
How Falcon 40B Instruct (40B params) fits at each quantization level on NVIDIA GH200 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B61 |
Q3_K_S | 3 | 19.6 GB | Low | B61 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Falcon 40B Instruct on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "tiiuae/falcon-40b-instruct" \
--hf-file "falcon-40b-instruct-Q5_K_M.gguf" \
-c 4096 -ngl 99Your hardware
