Can Falcon 40B Instruct run on NVIDIA H100 80GB?
YES — Runs Great
Falcon 40B Instruct needs ~39.8 GB VRAM. NVIDIA H100 80GB has 80.0 GB. With Q5_K_M quantization, expect ~100 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
108.4 tok/s
TTFT
1786 ms
Safe context
8K
Memory
39.8 GB / 80.0 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 | 108.4 tok/s | 974 ms | 8K |
| Coding | A | Runs well | 99.7 tok/s | 1943 ms | 8K |
| Agentic Coding | A | Runs well | 108.4 tok/s | 2598 ms | 8K |
| Reasoning | A | Runs well | 108.4 tok/s | 2111 ms | 8K |
| RAG | A | Runs well | 108.4 tok/s | 3248 ms | 8K |
Quantization options
How Falcon 40B Instruct (40B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B62 |
Q3_K_S | 3 | 19.6 GB | Low | B62 |
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
