Falcon 40B Instruct needs ~44.6 GB VRAM. Gaudi 3 128GB has 128.0 GB. With Q5_K_M quantization, expect ~100 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
99.8 tok/s
TTFT
1941 ms
Safe context
8K
Memory
44.6 GB / 128.0 GB
The raw memory story may look fine, but the software ecosystem is still a constraint here.
Runtime ecosystem is narrower than CUDA
Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.
Prefer CUDA if you want the path of least resistance
If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 99.8 tok/s | 1059 ms | 8K |
| Coding | B | Runs well | 99.8 tok/s | 1941 ms | 8K |
| Agentic Coding | A | Runs well | 99.8 tok/s | 2823 ms | 8K |
| Reasoning | B | Runs well | 99.8 tok/s | 2294 ms | 8K |
| RAG | A | Runs well | 99.8 tok/s | 3529 ms | 8K |
How Falcon 40B Instruct (40B params) fits at each quantization level on Gaudi 3 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B59 |
Q3_K_S | 3 | 19.6 GB | Low | B60 |
NVFP4 | 4 | 22.4 GB | Medium | B60 |
Q4_K_M | 4 | 24.4 GB | Medium | B60 |
Q5_K_M | 5 | 28.8 GB | High | B61 |
Q6_K | 6 | 32.8 GB | High | B62 |
Q8_0 | 8 | 42.8 GB | Very High | B63 |
F16Best for your GPU | 16 | 82.0 GB | Maximum | B68 |
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, Gaudi 3 128GB can run Falcon 40B Instruct with a B grade (Runs well). Expected decode speed: 99.8 tok/s.
Falcon 40B Instruct (40B parameters) requires approximately 44.6 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 Gaudi 3 128GB, Falcon 40B Instruct achieves approximately 99.8 tokens per second decode speed with a time-to-first-token of 1941ms using Q5_K_M quantization.
For coding workloads, Falcon 40B Instruct on Gaudi 3 128GB receives a B grade with 99.8 tok/s and 8K context.
On Gaudi 3 128GB, 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.
Prefer CUDA if you want the path of least resistance. If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/falcon-40b-instruct-on-gaudi-3-128gb" 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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