Can I Run / Qwen 2.5 Coder 7B / on NVIDIA RTX 4070 Super
Can I Run Qwen 2.5 Coder 7B on a NVIDIA RTX 4070 Super?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
7.6B
GPU memory
12.0GB
Smallest quant
Q2_K
Best fit
Q8_0
11 quantizations fit your 12.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 9.1 GB | 10.6 GB | 8.1 GB | +2.9 GB |
| Q6_K | 7.3 GB | 8.8 GB | 6.3 GB | +4.7 GB |
| Q5_K_M | 6.4 GB | 7.9 GB | 5.4 GB | +5.6 GB |
| Q5_K_S | 6.2 GB | 7.7 GB | 5.3 GB | +5.8 GB |
| Q4_K_M | 5.6 GB | 7.1 GB | 4.7 GB | +6.4 GB |
| Q4_K_S | 5.3 GB | 6.8 GB | 4.5 GB | +6.7 GB |
| Q4_0 | 5.3 GB | 6.8 GB | 4.4 GB | +6.7 GB |
| Q3_K_L | 4.4 GB | 5.9 GB | 4.1 GB | +7.6 GB |
| Q3_K_M | 4.2 GB | 5.7 GB | 3.8 GB | +7.8 GB |
| Q3_K_S | 3.9 GB | 5.4 GB | 3.5 GB | +8.1 GB |
| Q2_K | 3.5 GB | 5.0 GB | 3.0 GB | +8.5 GB |
Try it in the cloud first
Don't want to download Qwen 2.5 Coder 7B just to try it? Use a hosted API or rent a GPU by the second.
Affiliate links — we earn a commission at no cost to you.
Advertisement
Full model details
Qwen 2.5 Coder 7B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA RTX 4070 Super →
Top-ranked open-source models that fit in 12.0GB.
FAQ
Can the NVIDIA RTX 4070 Super run Qwen 2.5 Coder 7B?
Yes. The NVIDIA RTX 4070 Super's 12.0GB of VRAM is enough to run Qwen 2.5 Coder 7B at Q8_0 quantization (9.1GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 12.0GB. It uses about 9.1GB of memory and 10.6GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.