Qwen 2.5 14B needs ~14.0 GB VRAM. RTX 4080 Super 16GB has 16.0 GB. With Q4_K_M quantization, expect ~81 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
Tight fit
Decode
81.1 tok/s
TTFT
2387 ms
Safe context
27K
Memory
14.0 GB / 16.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 81.1 tok/s | 1302 ms | 27K |
| Coding | A | Tight fit | 81.1 tok/s | 2387 ms | 27K |
| Agentic Coding | A | Runs with offload (needs ~0.5 GB host RAM) | 54.2 tok/s | 5193 ms | 27K |
| Reasoning | A | Tight fit | 81.1 tok/s | 2821 ms | 27K |
| RAG | A | Runs with offload (needs ~0.5 GB host RAM) | 54.2 tok/s | 6492 ms | 27K |
How Qwen 2.5 14B (14B params) fits at each quantization level on RTX 4080 Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | A80 |
Q3_K_S | 3 | 6.9 GB | Low | A82 |
NVFP4 | 4 | 7.8 GB | Medium | A82 |
Q4_K_M | 4 | 8.5 GB | Medium | A82 |
Q5_K_M | 5 | 10.1 GB | High | A82 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | A82 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Copy-paste commands to run Qwen 2.5 14B on your machine.
Run
ollama run qwen2.5Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Phi-4-reasoning-plus 14B | 14.7B | S | 75.5 tok/s | |
 GPT-OSS 20B | 21B | A | 63.6 tok/s | |
 Codestral 2 25.08 | 22B | A | 18.6 tok/s | |
 CogVLM2 19B | 19B | A | 33.1 tok/s |
Yes, RTX 4080 Super 16GB can run Qwen 2.5 14B with a A grade (Tight fit). Expected decode speed: 81.1 tok/s.
Qwen 2.5 14B (14B parameters) requires approximately 14.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 14B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4080 Super 16GB, Qwen 2.5 14B achieves approximately 81.1 tokens per second decode speed with a time-to-first-token of 2387ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 14B on RTX 4080 Super 16GB receives a A grade with 81.1 tok/s and 27K context.
On RTX 4080 Super 16GB, Qwen 2.5 14B can safely use up to 27K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-2.5-14b-on-rtx-4080-super-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: