Can Qwen 3 32B run on Gaudi 3 128GB?
YES — Runs Great
Qwen 3 32B needs ~37.1 GB VRAM. Gaudi 3 128GB has 128.0 GB. With Q4_K_M quantization, expect ~144 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
144.3 tok/s
TTFT
1342 ms
Safe context
131K
Memory
37.1 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 | S | Runs well | 144.3 tok/s | 732 ms | 131K |
| Coding | S | Runs well | 144.3 tok/s | 1342 ms | 131K |
| Agentic Coding | S | Runs well | 132.7 tok/s | 2122 ms | 131K |
| Reasoning | S | Runs well | 144.3 tok/s | 1586 ms | 131K |
| RAG | S | Runs well | 144.3 tok/s | 2439 ms | 131K |
Quantization options
How Qwen 3 32B (32B params) fits at each quantization level on Gaudi 3 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | A80 |
Q3_K_S | 3 | 15.7 GB | Low | A80 |
NVFP4 | 4 | 17.9 GB | Medium | A80 |
Q4_K_M | 4 | 19.5 GB | Medium | A80 |
Q5_K_M | 5 | 23.0 GB | High | A80 |
Q6_K | 6 | 26.2 GB | High | A81 |
Q8_0 | 8 | 34.2 GB | Very High | A82 |
F16Best for your GPU | 16 | 65.6 GB | Maximum | S87 |
Get started
Copy-paste commands to run Qwen 3 32B on your machine.
Run
ollama run qwen3:32bYour hardware
More models your Gaudi 3 128GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 37.5 tok/s | ||
| 122B | S | 104.1 tok/s | ||
| 35B | S | 329.1 tok/s | ||
| 35B | S | 357.9 tok/s |
Frequently asked questions
Can Gaudi 3 128GB run Qwen 3 32B?
Yes, Gaudi 3 128GB can run Qwen 3 32B with a S grade (Runs well). Expected decode speed: 144.3 tok/s.
How much VRAM does Qwen 3 32B need?
Qwen 3 32B (32B parameters) requires approximately 37.1 GB of memory with Q4_K_M quantization.
What is the best quantization for Qwen 3 32B?
The recommended quantization for Qwen 3 32B is Q4_K_M, which balances quality and memory efficiency.
What speed will Qwen 3 32B run at on Gaudi 3 128GB?
On Gaudi 3 128GB, Qwen 3 32B achieves approximately 144.3 tokens per second decode speed with a time-to-first-token of 1342ms using Q4_K_M quantization.
Can Gaudi 3 128GB run Qwen 3 32B for coding?
For coding workloads, Qwen 3 32B on Gaudi 3 128GB receives a S grade with 144.3 tok/s and 131K context.
What context window can Qwen 3 32B use on Gaudi 3 128GB?
On Gaudi 3 128GB, Qwen 3 32B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
What should I upgrade first if Qwen 3 32B 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 Qwen 3 32B?
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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