QwenQwen 2.5 Coder 32B Instruct on NVIDIA RTX 4090 Laptop (150-175W)
RTX 4090 Laptop (150-175W) runs Qwen 2.5 Coder 32B Instruct at Q3_K_M — 9 tok/s due to limited memory bandwidth. Slow but functional — see all options below.
Model Size
32.5B
Device VRAM
16 GB
Bandwidth
512 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Qwen 2.5 Coder 32B Instruct on NVIDIA RTX 4090 Laptop (150-175W) at Q3_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | 9 tok/s | 941ms | ✓ Yes | Marginal | estimated |
Notes
Q3_K_M
Sustained post-thermal-throttle performance. TDP-capped laptop variant.
About Qwen 2.5 Coder 32B Instruct
Qwen 2.5 Coder 32B Instruct (32.5B) is a coding, ai coding, ai building model. The coding model that defines the builder workflow. Matches GPT-4 on HumanEval. This is what Cursor and Continue.dev users run locally when they want to eliminate API dependency. Apache 2.0 license. The cornerstone of the 'Full AI Builder' profile.
View all Qwen 2.5 Coder 32B Instruct hardware options →About NVIDIA RTX 4090 Laptop (150-175W)
NVIDIA RTX 4090 Laptop (150-175W) has 16 GB at 512 GB/s. Street price: $0.
See all models NVIDIA RTX 4090 Laptop (150-175W) can run →Estimate method: Community laptop benchmarks and thermal throttle reports. Reference hardware source: reddit.com (2026-03-14)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.