Can Qwen 3 30B A3B run on Tesla P40 24GB?
YES — With Offload
Qwen 3 30B A3B needs ~23.7 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~31 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 with offload
Decode
30.9 tok/s
TTFT
6272 ms
Safe context
20K
Memory
23.7 GB / 24.0 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
Best improvement path
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs with offload | 30.9 tok/s | 3421 ms | 20K |
| Coding | S | Runs with offload | 30.9 tok/s | 6272 ms | 20K |
| Agentic Coding | S | Runs with offload | 18.7 tok/s | 15053 ms | 20K |
| Reasoning | S | Runs with offload | 30.9 tok/s | 7412 ms | 20K |
| RAG | S | Runs with offload (needs ~0.8 GB host RAM) | 20.3 tok/s | 17303 ms | 20K |
Quantization options
How Qwen 3 30B A3B (30.5B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | S91 |
Q3_K_S | 3 | 14.9 GB | Low | S90 |
NVFP4 | 4 | 17.1 GB | Medium | S90 |
Q4_K_MBest for your GPU | 4 | 18.6 GB | Medium | S90 |
Q5_K_M | 5 | 22.0 GB | High | F0 |
Q6_K | 6 | 25.0 GB | High | F0 |
Q8_0 | 8 | 32.6 GB | Very High | F0 |
F16 | 16 | 62.5 GB | Maximum | F0 |
Get started
Copy-paste commands to run Qwen 3 30B A3B on your machine.
Run
ollama run qwen3:30b-a3bYour hardware
More models your Tesla P40 24GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 35B | A | 16.7 tok/s | ||
| 32B | A | 6.4 tok/s |
Frequently asked questions
Can Tesla P40 24GB run Qwen 3 30B A3B?
Yes, Tesla P40 24GB can run Qwen 3 30B A3B with a S grade (Runs with offload). Expected decode speed: 30.9 tok/s.
How much VRAM does Qwen 3 30B A3B need?
Qwen 3 30B A3B (30.5B parameters) requires approximately 23.7 GB of memory with Q4_K_M quantization.
What is the best quantization for Qwen 3 30B A3B?
The recommended quantization for Qwen 3 30B A3B is Q4_K_M, which balances quality and memory efficiency.
What speed will Qwen 3 30B A3B run at on Tesla P40 24GB?
On Tesla P40 24GB, Qwen 3 30B A3B achieves approximately 30.9 tokens per second decode speed with a time-to-first-token of 6272ms using Q4_K_M quantization.
Can Tesla P40 24GB run Qwen 3 30B A3B for coding?
For coding workloads, Qwen 3 30B A3B on Tesla P40 24GB receives a S grade with 30.9 tok/s and 20K context.
What context window can Qwen 3 30B A3B use on Tesla P40 24GB?
On Tesla P40 24GB, Qwen 3 30B A3B can safely use up to 20K 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 30B A3B feels slow on Tesla P40 24GB?
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Embed this result▼
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<iframe src="https://willitrunai.com/embed/qwen-3-30b-a3b-on-tesla-p40-24gb" 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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