Can Falcon 40B Instruct run on Gaudi 3 128GB?
YES — Runs Great
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
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
99.8 tok/s
TTFT
1941 ms
Safe context
8K
Memory
44.6 GB / 128.0 GB
Memory breakdown
See how fast it feels
What limits this setup
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.
Best improvement path
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.
Performance by workload
| 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 |
Quantization options
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 |
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 99Frequently asked questions
Can Gaudi 3 128GB run Falcon 40B Instruct?
Yes, Gaudi 3 128GB can run Falcon 40B Instruct with a B grade (Runs well). Expected decode speed: 99.8 tok/s.
How much VRAM does Falcon 40B Instruct need?
Falcon 40B Instruct (40B parameters) requires approximately 44.6 GB of memory with Q5_K_M quantization.
What is the best quantization for Falcon 40B Instruct?
The recommended quantization for Falcon 40B Instruct is Q5_K_M, which balances quality and memory efficiency.
What speed will Falcon 40B Instruct run at on Gaudi 3 128GB?
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.
Can Gaudi 3 128GB run Falcon 40B Instruct for coding?
For coding workloads, Falcon 40B Instruct on Gaudi 3 128GB receives a B grade with 99.8 tok/s and 8K context.
What context window can Falcon 40B Instruct use on Gaudi 3 128GB?
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.
What should I upgrade first if Falcon 40B Instruct feels slow on Gaudi 3 128GB?
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.
Would CUDA be a better path than Gaudi 3 128GB for Falcon 40B Instruct?
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.
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