Qwen 2.5 7B needs ~7.1 GB VRAM. RTX 2060 Super 8GB has 8.0 GB. With Q4_K_M quantization, expect ~66 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
66.1 tok/s
TTFT
2930 ms
Safe context
32K
Memory
7.1 GB / 8.0 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 66.1 tok/s | 1598 ms | 32K |
| Coding | A | Tight fit | 66.1 tok/s | 2930 ms | 32K |
| Agentic Coding | A | Runs with offload | 66.1 tok/s | 4262 ms | 32K |
| Reasoning | A | Tight fit | 66.1 tok/s | 3463 ms | 32K |
| RAG | A | Runs with offload | 66.1 tok/s | 5328 ms | 32K |
How Qwen 2.5 7B (7B params) fits at each quantization level on RTX 2060 Super 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | A79 |
Q3_K_S | 3 | 3.4 GB | Low | A79 |
NVFP4 | 4 | 3.9 GB | Medium | A79 |
Q4_K_M | 4 | 4.3 GB | Medium | A79 |
Q5_K_MBest for your GPU | 5 | 5.0 GB | High | A79 |
Q6_K | 6 | 5.7 GB | High | F0 |
Q8_0 | 8 | 7.5 GB | Very High | F0 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run Qwen 2.5 7B on your machine.
Run
ollama run qwen2.5Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3 8B | 8B | A | 31.6 tok/s | |
 Nemotron Nano 8B | 8B | A | 33.6 tok/s | |
 InternVL2 8B | 8B | A | 33.6 tok/s | |
 Ministral 3 8B | 8B | A | 31.6 tok/s | |
 MiniCPM-V 2.6 8B | 8B | A | 33.6 tok/s |
Yes, RTX 2060 Super 8GB can run Qwen 2.5 7B with a A grade (Tight fit). Expected decode speed: 66.1 tok/s.
Qwen 2.5 7B (7B parameters) requires approximately 7.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 7B is Q4_K_M, which balances quality and memory efficiency.
On RTX 2060 Super 8GB, Qwen 2.5 7B achieves approximately 66.1 tokens per second decode speed with a time-to-first-token of 2930ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 7B on RTX 2060 Super 8GB receives a A grade with 66.1 tok/s and 32K context.
On RTX 2060 Super 8GB, Qwen 2.5 7B can safely use up to 32K 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-2.5-7b-on-rtx-2060-super-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: