Qwen 2.5 3B needs ~5.7 GB VRAM. RTX 3000 Ada Laptop 8GB has 8.0 GB. With Q4_K_M quantization, expect ~48 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
Runs well
Decode
48.0 tok/s
TTFT
4033 ms
Safe context
33K
Memory
5.7 GB / 8.0 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 | A | Runs well | 48.0 tok/s | 2200 ms | 33K |
| Coding | A | Runs well | 48.0 tok/s | 4033 ms | 33K |
| Agentic Coding | A | Runs with offload | 48.0 tok/s | 5867 ms | 33K |
| Reasoning | A | Runs well | 48.0 tok/s | 4767 ms | 33K |
| RAG | A | Runs with offload | 48.0 tok/s | 7333 ms | 33K |
How Qwen 2.5 3B (3B params) fits at each quantization level on RTX 3000 Ada Laptop 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | B69 |
Q3_K_S | 3 | 1.5 GB | Low | B70 |
NVFP4 | 4 | 1.7 GB | Medium | A70 |
Q4_K_M | 4 | 1.8 GB | Medium | A70 |
Q5_K_M | 5 | 2.2 GB | High | A71 |
Q6_K | 6 | 2.5 GB | High | A72 |
Q8_0Best for your GPU | 8 | 3.2 GB | Very High | A73 |
F16 | 16 | 6.1 GB | Maximum | F0 |
Copy-paste commands to run Qwen 2.5 3B on your machine.
Run
ollama run qwen2.5:3bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | A | 20.3 tok/s | |
| Qwen 3.5 4B | 4B | S | 64 tok/s | |
| Qwen 3 8B | 8B | A | 26.3 tok/s | |
 Phi-4 Mini Reasoning 4B | 3.8B | S | 60.8 tok/s | |
 Nemotron Nano 8B | 8B | A | 27.9 tok/s |
Yes, RTX 3000 Ada Laptop 8GB can run Qwen 2.5 3B with a A grade (Runs well). Expected decode speed: 48.0 tok/s.
Qwen 2.5 3B (3B parameters) requires approximately 5.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 3B is Q4_K_M, which balances quality and memory efficiency.
On RTX 3000 Ada Laptop 8GB, Qwen 2.5 3B achieves approximately 48.0 tokens per second decode speed with a time-to-first-token of 4033ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 3B on RTX 3000 Ada Laptop 8GB receives a A grade with 48.0 tok/s and 33K context.
On RTX 3000 Ada Laptop 8GB, Qwen 2.5 3B can safely use up to 33K 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-2.5-3b-on-rtx-3000-ada-laptop-8gb" 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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