Qwen3-Coder — Local AI Model by Alibaba Cloud

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 10 lipca 2026

Alibaba's dedicated coding line. The 480B-A35B flagship holds state-of-the-art among open models on SWE-bench Verified and agentic coding at release (Qwen positions it comparable to Claude Sonnet 4), while the 80B-A3B variant delivers most of that quality with only 3B active parameters — cheap enough to self-host. Best-in-class open weights for repo-level coding, debugging, and code review.

Hardware Requirements

Qwen3-Coder 8B	Min 6 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run qwen3-coder:8b`
Qwen3-Coder 80B-A3B (MoE)	Min 49 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run qwen3-coder:80b-a3b-q4`
Qwen3-Coder 480B-A35B (MoE)	Min 291 GB VRAM · Q4_K_M · 256,000 ctx · `ollama run qwen3-coder:480b-a35b`

Recommended GPU

The cheapest GPU that runs Qwen3-Coder locally (min 6 GB VRAM) is the Intel Arc B570 (10 GB).

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.

Intel Arc B570 10GB

Sugerowana cena premierowa: $219

Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.

Sprawdź cenę na Amazon

How to Run Locally

Install Ollama then run: ollama run qwen3-coder:8b

Minimum VRAM: 6 GB. For best results use Q4_K_M quantization.

Qwen3-Coder — Frequently Asked Questions

How much VRAM does Qwen3-Coder need?

Qwen3-Coder needs about 6 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Qwen3-Coder 8B (6 GB, Q4_K_M); Qwen3-Coder 80B-A3B (MoE) (49 GB, Q4_K_M); Qwen3-Coder 480B-A35B (MoE) (291 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Qwen3-Coder on an RTX 4090 (24 GB)?

Yes — Qwen3-Coder runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.

What quantization should I use for Qwen3-Coder?

Q4_K_M is the best balance of quality and VRAM for Qwen3-Coder in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run Qwen3-Coder with Ollama?

Install Ollama, then run: ollama run qwen3-coder:8b. This downloads Qwen3-Coder and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.