Can I Run Qwen 2.5 Coder 7B Instruct on NVIDIA GeForce RTX 4060 Ti (16GB GDDR6)?
Full VRAM footprint analysis, tokens/sec generation benchmark, and copy-paste Ollama & vLLM runtime commands for running Qwen 2.5 Coder 7B Instruct (7.6B) on NVIDIA GeForce RTX 4060 Ti (16GB GDDR6) (16 GB).
✓ Fits Comfortably in VRAM
Local Hardware Configurations & Pricing
NVIDIA GeForce RTX 5090 (32GB GDDR7)
Maximum tokens/sec on 27B–35B models & Blackwell FP4 quantization
NVIDIA GeForce RTX 4090 (24GB GDDR6X)
The 24GB CUDA enthusiast standard for 14B–32B Q4_K_M models
2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM)
Best price-to-VRAM homelab rig for Llama 3.3 70B Q4_K_M & Qwen 2.5 Coder 32B Q8_0
NVIDIA GeForce RTX 4060 Ti (16GB GDDR6)
Lowest-cost 16GB VRAM GPU for running 8B–14B models and LoRA fine-tuning on a budget
Cloud Instance Options for Qwen 2.5 Coder 7B Instruct
On-DemandDeploy this model on an on-demand cloud GPU without local hardware constraints or power usage:
Quantization Precision Matrix
32K ctx • KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 15.2 GB | 0.94 GB | 17.42 GB (109%) | ~3 t/s | PARTIAL |
| Q8_08.5 bpw | 8.06 GB | 0.94 GB | 10.03 GB (63%) | ~23 t/s | FITS |
| Q6_K6.56 bpw | 6.23 GB | 0.94 GB | 8.14 GB (51%) | ~29 t/s | FITS |
| Q5_K_M5.68 bpw | 5.4 GB | 0.94 GB | 7.28 GB (46%) | ~33 t/s | FITS |
| Q4_K_M4.8 bpw | 4.56 GB | 0.94 GB | 6.41 GB (40%) | ~39 t/s | FITS |
| FP44.25 bpw | 4.03 GB | 0.94 GB | 5.86 GB (37%) | ~44 t/s | FITS |
| IQ3_XS3.3 bpw | 3.12 GB | 0.94 GB | 4.92 GB (31%) | ~56 t/s | FITS |
Frequently Asked Questions: Qwen 2.5 Coder 7B Instruct on NVIDIA GeForce RTX 4060 Ti (16GB GDDR6)
How much VRAM does Qwen 2.5 Coder 7B Instruct need on NVIDIA GeForce RTX 4060 Ti (16GB GDDR6)?
At standard 4-bit quantization (Q4_K_M) with 32K context, Qwen 2.5 Coder 7B Instruct requires 6.41 GB of total VRAM (weights + KV cache + CUDA runtime overhead).
What inference speed will Qwen 2.5 Coder 7B Instruct achieve on NVIDIA GeForce RTX 4060 Ti (16GB GDDR6)?
Based on NVIDIA GeForce RTX 4060 Ti (16GB GDDR6)'s 288 GB/s memory bandwidth, expected decode speed is approximately 39 tokens per second.
Can I expand context beyond 32K tokens?
Each additional 32K tokens of context requires additional KV cache memory. For longer context windows, consider 8-bit or 4-bit KV cache quantization.