Can Qwen 2.5 14B run on Tesla P40 24GB?
YES — Runs Great
Qwen 2.5 14B needs ~15.1 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~26 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
25.8 tok/s
TTFT
7499 ms
Safe context
65K
Memory
15.1 GB / 24.0 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
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
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 25.8 tok/s | 4090 ms | 65K |
| Coding | A | Runs well | 25.8 tok/s | 7499 ms | 65K |
| Agentic Coding | A | Runs well | 23.9 tok/s | 11780 ms | 65K |
| Reasoning | A | Runs well | 25.8 tok/s | 8863 ms | 65K |
| RAG | A | Runs well | 25.8 tok/s | 13635 ms | 65K |
Quantization options
How Qwen 2.5 14B (14B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | A77 |
Q3_K_S | 3 | 6.9 GB | Low | A77 |
NVFP4 | 4 | 7.8 GB | Medium | A78 |
Q4_K_M | 4 | 8.5 GB | Medium | A78 |
Q5_K_M | 5 | 10.1 GB | High | A79 |
Q6_K | 6 | 11.5 GB | High | A80 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | A81 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Get started
Copy-paste commands to run Qwen 2.5 14B on your machine.
Run
ollama run qwen2.5Your hardware
More models your Tesla P40 24GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 30.9 tok/s | ||
| 27B | S | 13.4 tok/s | ||
| 27B | S | 13.4 tok/s | ||
| 30B | S | 31.9 tok/s | ||
| 35B | A | 16.7 tok/s |
Frequently asked questions
Can Tesla P40 24GB run Qwen 2.5 14B?
Yes, Tesla P40 24GB can run Qwen 2.5 14B with a A grade (Runs well). Expected decode speed: 25.8 tok/s.
How much VRAM does Qwen 2.5 14B need?
Qwen 2.5 14B (14B parameters) requires approximately 15.1 GB of memory with Q4_K_M quantization.
What is the best quantization for Qwen 2.5 14B?
The recommended quantization for Qwen 2.5 14B is Q4_K_M, which balances quality and memory efficiency.
What speed will Qwen 2.5 14B run at on Tesla P40 24GB?
On Tesla P40 24GB, Qwen 2.5 14B achieves approximately 25.8 tokens per second decode speed with a time-to-first-token of 7499ms using Q4_K_M quantization.
Can Tesla P40 24GB run Qwen 2.5 14B for coding?
For coding workloads, Qwen 2.5 14B on Tesla P40 24GB receives a A grade with 25.8 tok/s and 65K context.
What context window can Qwen 2.5 14B use on Tesla P40 24GB?
On Tesla P40 24GB, Qwen 2.5 14B can safely use up to 65K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Embed this result▼
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<iframe src="https://willitrunai.com/embed/qwen-2.5-14b-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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