Qwen3 Next 80B A3B Thinking — Hardware Requirements & GPU Compatibility
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Qwen3 Next 80B A3B Thinking is a 81.3B-parameter open language model from Alibaba in the Qwen family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 49.20 GB of VRAM — see which GPUs and Macs can run it below.
31.0K downloads
489 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen
- Parameters
- 81.3B
- Architecture
- Qwen3NextForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 151,936
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3 Next 80B A3B Thinking Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 35.0 GB | 47.8 GB | 34.56 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 36.0 GB | 48.8 GB | 35.58 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 40.0 GB | 52.8 GB | 39.65 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 41.1 GB | 53.9 GB | 40.66 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 49.2 GB | 62.0 GB | 48.79 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 58.3 GB | 71.1 GB | 57.94 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 67.5 GB | 80.3 GB | 67.09 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 81.7 GB | 94.5 GB | 81.32 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Qwen3 Next 80B A3B Thinking?
Q4_K_M · 49.2 GBQwen3 Next 80B A3B Thinking (Q4_K_M) requires 49.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 64+ GB is recommended. Using the full 262K context window can add up to 12.8 GB, bringing total usage to 62.0 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3 Next 80B A3B Thinking?
Q4_K_M · 49.2 GB8 devices with unified memory can run Qwen3 Next 80B A3B Thinking, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightBenchmarks
View all 3 →Related Models
Derivatives (8)
Frequently Asked Questions
- How much VRAM does Qwen3 Next 80B A3B Thinking need?
Qwen3 Next 80B A3B Thinking requires 49.2 GB of VRAM at Q4_K_M, or 81.7 GB at Q8_0. Full 262K context adds up to 12.8 GB (62.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 81.3B × 4.8 bits ÷ 8 = 48.8 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_M49.2 GBQ4_K_M + full context62.0 GB- Can NVIDIA GeForce RTX 4090 run Qwen3 Next 80B A3B Thinking?
Yes, at IQ2_XXS (22.8 GB) or lower. Higher quantizations like IQ2_XS (24.8 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Qwen3 Next 80B A3B Thinking?
For Qwen3 Next 80B A3B Thinking, Q4_K_M (49.2 GB) offers the best balance of quality and VRAM usage. Q4_K_L (50.2 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 22.8 GB.
VRAM requirement by quantization
IQ2_XXS22.8 GBQ2_K35.0 GBQ3_K_L42.1 GBQ4_K_M ★49.2 GBQ4_K_L50.2 GBQ8_081.7 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3 Next 80B A3B Thinking on a Mac?
Qwen3 Next 80B A3B Thinking requires at least 22.8 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 Next 80B A3B Thinking locally?
Yes — Qwen3 Next 80B A3B Thinking can run locally on consumer hardware. At Q4_K_M quantization it needs 49.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3 Next 80B A3B Thinking?
At Q4_K_M, Qwen3 Next 80B A3B Thinking can reach ~59 tok/s on AMD Instinct MI300X. 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 ÷ 49.2 × 0.55 = ~59 tok/s
Estimated speed at Q4_K_M (49.2 GB)
~59 tok/s~44 tok/s~37 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3 Next 80B A3B Thinking?
At Q4_K_M, the download is about 48.79 GB. The full-precision Q8_0 version is 81.32 GB. The smallest option (IQ2_XXS) is 22.36 GB.
- Which GPUs can run Qwen3 Next 80B A3B Thinking?
No single consumer GPU has enough VRAM to run Qwen3 Next 80B A3B Thinking at Q4_K_M (49.2 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3 Next 80B A3B Thinking?
8 devices with unified memory can run Qwen3 Next 80B A3B Thinking at Q4_K_M (49.2 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), Mac Studio M4 Max (64 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.