Qwen 2.5 7B needs ~7.1 GB VRAM. RTX 4060 8GB has 8.0 GB. With Q4_K_M quantization, expect ~51 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
50.5 tok/s
TTFT
3835 ms
Safe context
32K
Memory
7.1 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 | Tight fit | 50.5 tok/s | 2092 ms | 32K |
| Coding | A | Tight fit | 50.5 tok/s | 3835 ms | 32K |
| Agentic Coding | A | Runs with offload | 50.5 tok/s | 5578 ms | 32K |
| Reasoning | A | Tight fit | 50.5 tok/s | 4532 ms | 32K |
| RAG | A | Runs with offload | 50.5 tok/s | 6972 ms | 32K |
Inference speed
Estimated decode speed (tokens/sec) for Qwen 2.5 7B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~98 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 98.0 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 98.0 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 98.0 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 98.0 | Fits |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 98.0 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 98.0 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 98.0 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 98.0 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 96.1 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 95.3 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 95.3 | Fits |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 61.0 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 60.4 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 55.9 | Fits |
| RTX 4060 8GB | 8 GB | Q4_K_M | 50.5 | Tight |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 49.2 | Fits |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How Qwen 2.5 7B (7B params) fits at each quantization level on RTX 4060 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 | 25.1 tok/s | |
| Nemotron Nano 8B | 8B | A | 26.6 tok/s | |
 InternVL2 8B | 8B | A | 26.6 tok/s | |
 Ministral 3 8B | 8B | A | 25.1 tok/s | |
 MiniCPM-V 2.6 8B | 8B | A | 26.6 tok/s |
Yes, RTX 4060 8GB can run Qwen 2.5 7B with a A grade (Tight fit). Expected decode speed: 50.5 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 4060 8GB, Qwen 2.5 7B achieves approximately 50.5 tokens per second decode speed with a time-to-first-token of 3835ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 7B on RTX 4060 8GB receives a A grade with 50.5 tok/s and 32K context.
On RTX 4060 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-4060-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: