Qwen3 Code Reasoning 4B — Hardware Requirements & GPU Compatibility
ChatCodeReasoning
284 downloads
15 likesSpecifications
- Publisher
- GetSoloTech
- Family
- Qwen
- Parameters
- 4B
- Architecture
- Qwen3ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2025-08-25
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3 Code Reasoning 4B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 8.5 GB | 32.5 GB | 8.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Qwen3 Code Reasoning 4B?
BF16 · 8.5 GBQwen3 Code Reasoning 4B (BF16) requires 8.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 12+ GB is recommended. Using the full 262K context window can add up to 24.0 GB, bringing total usage to 32.5 GB. 28 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Qwen3 Code Reasoning 4B?
BF16 · 8.5 GB27 devices with unified memory can run Qwen3 Code Reasoning 4B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 Code Reasoning 4B need?
Qwen3 Code Reasoning 4B requires 8.5 GB of VRAM at BF16. Full 262K context adds up to 24.0 GB (32.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 4B × 16 bits ÷ 8 = 8 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 24.5 GB (at full 262K context)
VRAM usage by quantization
BF168.5 GBBF16 + full context32.5 GB- Can I run Qwen3 Code Reasoning 4B on a Mac?
Qwen3 Code Reasoning 4B requires at least 8.5 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen3 Code Reasoning 4B locally?
Yes — Qwen3 Code Reasoning 4B can run locally on consumer hardware. At BF16 quantization it needs 8.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3 Code Reasoning 4B?
At BF16, Qwen3 Code Reasoning 4B can reach ~343 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~77 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 8.5 × 0.55 = ~343 tok/s
Estimated speed at BF16 (8.5 GB)
AMD Instinct MI300X~343 tok/sNVIDIA GeForce RTX 4090~77 tok/sNVIDIA H100 SXM~257 tok/sAMD Instinct MI250X~212 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3 Code Reasoning 4B?
At BF16, the download is about 8.00 GB.
- Which GPUs can run Qwen3 Code Reasoning 4B?
28 consumer GPUs can run Qwen3 Code Reasoning 4B at BF16 (8.5 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 17 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen3 Code Reasoning 4B?
27 devices with unified memory can run Qwen3 Code Reasoning 4B at BF16 (8.5 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.