Falcon 40B Instruct needs ~51.0 GB VRAM. NVIDIA GB200 192GB has 192.0 GB. With Q5_K_M quantization, expect ~259 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
258.8 tok/s
TTFT
748 ms
Safe context
8K
Memory
51.0 GB / 192.0 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 | B | Runs well | 258.8 tok/s | 408 ms | 8K |
| Coding | B | Runs well | 258.8 tok/s | 748 ms | 8K |
| Agentic Coding | B | Runs well | 258.8 tok/s | 1088 ms | 8K |
| Reasoning | B | Runs well | 258.8 tok/s | 884 ms | 8K |
| RAG | B | Runs well | 258.8 tok/s | 1360 ms | 8K |
How Falcon 40B Instruct (40B params) fits at each quantization level on NVIDIA GB200 192GB (192.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B58 |
Q3_K_S | 3 | 19.6 GB | Low | B58 |
NVFP4 | 4 | 22.4 GB | Medium | B58 |
Q4_K_M | 4 | 24.4 GB | Medium | B59 |
Q5_K_M | 5 | 28.8 GB | High | B59 |
Q6_K | 6 | 32.8 GB | High | B60 |
Q8_0 | 8 | 42.8 GB | Very High | B61 |
F16Best for your GPU | 16 | 82.0 GB | Maximum | B65 |
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 99Yes, NVIDIA GB200 192GB can run Falcon 40B Instruct with a B grade (Runs well). Expected decode speed: 258.8 tok/s.
Falcon 40B Instruct (40B parameters) requires approximately 51.0 GB of memory with Q5_K_M quantization.
The recommended quantization for Falcon 40B Instruct is Q5_K_M, which balances quality and memory efficiency.
On NVIDIA GB200 192GB, Falcon 40B Instruct achieves approximately 258.8 tokens per second decode speed with a time-to-first-token of 748ms using Q5_K_M quantization.
For coding workloads, Falcon 40B Instruct on NVIDIA GB200 192GB receives a B grade with 258.8 tok/s and 8K context.
On NVIDIA GB200 192GB, Falcon 40B Instruct can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/falcon-40b-instruct-on-gb200-192gb" 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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