Qwen3 Coder Next Int4 AutoRound — Hardware Requirements & GPU Compatibility
ChatCode
11.9K downloads
18 likesSpecifications
- Publisher
- Intel
- Family
- Qwen
- Parameters
- 11.8B
- Architecture
- Qwen3NextForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2026-02-10
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HuggingFace
How Much VRAM Does Qwen3 Coder Next Int4 AutoRound Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 5.4 GB | 18.2 GB | 5.03 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 5.6 GB | 18.4 GB | 5.17 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 6.2 GB | 18.9 GB | 5.76 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 6.3 GB | 19.1 GB | 5.91 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 7.5 GB | 20.3 GB | 7.09 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 8.8 GB | 21.6 GB | 8.42 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 10.2 GB | 22.9 GB | 9.75 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 12.2 GB | 25.0 GB | 11.82 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Qwen3 Coder Next Int4 AutoRound?
Q4_K_M · 7.5 GBQwen3 Coder Next Int4 AutoRound (Q4_K_M) requires 7.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 10+ GB is recommended. Using the full 262K context window can add up to 12.8 GB, bringing total usage to 20.3 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Qwen3 Coder Next Int4 AutoRound?
Q4_K_M · 7.5 GB33 devices with unified memory can run Qwen3 Coder Next Int4 AutoRound, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 Coder Next Int4 AutoRound need?
Qwen3 Coder Next Int4 AutoRound requires 7.5 GB of VRAM at Q4_K_M, or 12.2 GB at Q8_0. Full 262K context adds up to 12.8 GB (20.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 11.8B × 4.8 bits ÷ 8 = 7.1 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 13.2 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M7.5 GBQ4_K_M + full context20.3 GB- What's the best quantization for Qwen3 Coder Next Int4 AutoRound?
For Qwen3 Coder Next Int4 AutoRound, Q4_K_M (7.5 GB) offers the best balance of quality and VRAM usage. Q4_K_L (7.6 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 3.6 GB.
VRAM requirement by quantization
IQ2_XXS3.6 GB~53%IQ3_S5.4 GB~75%Q3_K_L6.5 GB~86%Q4_K_M ★7.5 GB~89%Q4_K_L7.6 GB~90%Q8_012.2 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3 Coder Next Int4 AutoRound on a Mac?
Qwen3 Coder Next Int4 AutoRound requires at least 3.6 GB at IQ2_XXS, 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 Coder Next Int4 AutoRound locally?
Yes — Qwen3 Coder Next Int4 AutoRound can run locally on consumer hardware. At Q4_K_M quantization it needs 7.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3 Coder Next Int4 AutoRound?
At Q4_K_M, Qwen3 Coder Next Int4 AutoRound can reach ~389 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~87 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 ÷ 7.5 × 0.55 = ~389 tok/s
Estimated speed at Q4_K_M (7.5 GB)
AMD Instinct MI300X~389 tok/sNVIDIA GeForce RTX 4090~87 tok/sNVIDIA H100 SXM~291 tok/sAMD Instinct MI250X~240 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3 Coder Next Int4 AutoRound?
At Q4_K_M, the download is about 7.09 GB. The full-precision Q8_0 version is 11.82 GB. The smallest option (IQ2_XXS) is 3.25 GB.
- Which GPUs can run Qwen3 Coder Next Int4 AutoRound?
35 consumer GPUs can run Qwen3 Coder Next Int4 AutoRound at Q4_K_M (7.5 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 26 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen3 Coder Next Int4 AutoRound?
33 devices with unified memory can run Qwen3 Coder Next Int4 AutoRound at Q4_K_M (7.5 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.