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Model · Alibaba Qwen

Qwen3 30B-A3B: VRAM and hardware requirements

At Q4_K_M with an 8K context, Qwen3 30B-A3B needs about 19.9 GB: a GPU with 24 GB or more runs it entirely in VRAM.

  • Parameters30.5B
  • Active3.3B
  • Max context128K
  • LicenseApache-2.0

Specifications

Organization
Alibaba Qwen
Architecture
qwen3_moe
Released
April 2025
Layers
48
Hidden size
2048
Attention heads
32
KV heads
4
Head dimension
128
Vocabulary
151,936
KV cache per 1K tokens (f16)
0.094 GB

Official specData updated 24 days agoSource: Hugging Face config.json + model card

Quantizations and memory

Qwen3 30B-A3B: memory by quantization at 8K context
QuantizationFile sizeMemory neededMinimum GPU memoryQuality
BF1656.9 GB~61.2 GB80 GBReference (unquantized)
Q8_030.3 GB~33.3 GB48 GBNear-lossless
Q6_K23.4 GB~26.1 GB32 GBNear-lossless
Q5_K_M20.2 GB~22.8 GB24 GBVery good
Q4_K_MMost used17.3 GB~19.9 GB24 GBGood — the usual choice
IQ4_XS15.3 GB~18.2 GB20 GBGood — the usual choice
Q3_K_M13.1 GB~16.5 GB16 GBNoticeable loss
Q2_K10.2 GB~13.4 GB16 GBSignificant loss

File sizes: not available until imported from the model repository. Memory = weights (estimated from bits per weight) + KV cache + runtime overhead + safety margin. (BF16 ≈ 16 bpw, Q8_0 ≈ 8.5 bpw, Q6_K ≈ 6.57 bpw, Q5_K_M ≈ 5.7 bpw, Q4_K_M ≈ 4.9 bpw, IQ4_XS ≈ 4.46 bpw, Q3_K_M ≈ 4 bpw, Q2_K ≈ 3.17 bpw)

Q4, Q5 or Q8: how to choose a quantization

GPUs that run Qwen3 30B-A3B

Qwen3 30B-A3B Q4_K_M · 8K context, one GPU
RTX 509032 GB · 64 GB RAM~19.7 GB · 156–284 tok/s estimateExcellent
RTX 409024 GB · 64 GB RAM~19.7 GB · 125–209 tok/s estimateExcellent
RTX 309024 GB · 64 GB RAM~19.7 GB · 120–200 tok/s estimateExcellent
RX 7900 XTX24 GB · 64 GB RAM~19.8 GB · 81–149 tok/s estimateCompatible
RTX 5060 Ti 16 GB16 GB · 64 GB RAM~19.7 GB · 25–49 tok/s estimateCPU/GPU offload
RTX 5070 Ti16 GB · 64 GB RAM~19.7 GB · 28–56 tok/s estimateCPU/GPU offload
RTX 508016 GB · 64 GB RAM~19.7 GB · 28–57 tok/s estimateCPU/GPU offload
RTX 4060 Ti 16 GB16 GB · 64 GB RAM~19.7 GB · 23–43 tok/s estimateCPU/GPU offload
RTX 4070 Ti SUPER16 GB · 64 GB RAM~19.7 GB · 27–54 tok/s estimateCPU/GPU offload
RX 9070 XT16 GB · 64 GB RAM~19.8 GB · 23–48 tok/s estimateCPU/GPU offload
RTX 3060 12 GB12 GB · 64 GB RAM~19.7 GB · 16–31 tok/s estimateCPU/GPU offload
RTX 407012 GB · 64 GB RAM~19.7 GB · 17–32 tok/s estimateCPU/GPU offload
RTX 507012 GB · 64 GB RAM~19.7 GB · 17–33 tok/s estimateCPU/GPU offload
RTX 40608 GB · 64 GB RAM~19.7 GB · 12–23 tok/s estimatePossible but slow

Macs that run Qwen3 30B-A3B

Qwen3 30B-A3B Q4_K_M · 8K context
M3 Ultra (80-core GPU) · 512 GBMac Studio~19.5 GB · 61–112 tok/s estimateExcellent
M4 Max (40-core GPU) · 128 GBMacBook Pro 14, MacBook Pro 16~19.5 GB · 53–93 tok/s estimateExcellent
M3 Max (40-core GPU) · 128 GBMacBook Pro 14, MacBook Pro 16~19.5 GB · 46–78 tok/s estimateExcellent
M4 Pro (20-core GPU) · 64 GBMac mini, MacBook Pro 14~19.5 GB · 38–62 tok/s estimateExcellent
M4 Max (32-core GPU) · 36 GBMacBook Pro 14, MacBook Pro 16~19.5 GB · 47–79 tok/s estimateExcellent
M4 · 32 GBMacBook Air, MacBook Pro 14~19.5 GB · 22–33 tok/s estimateCompatible
M5 · 32 GBMacBook Pro 14~19.5 GB · 26–40 tok/s estimateCompatible
M3 · 24 GBMacBook Air, MacBook Pro 14~19.5 GB · No dataIncompatible

EstimateData updated 24 days agoSource: Run LLM Locally engine

Limits in plain words

Qwen3 30B-A3B is a mixture-of-experts model: all 30.5B parameters must be in memory, but only 3.3B are read per token, so it generates much faster than a dense model of the same size.

The KV cache grows with context: at 32K it adds about 3 GB on top of the weights.

With under 8 GB of VRAM, use a smaller quantization or a smaller model of the same family.

Where to buy

Prices and links follow the market you choose.

Radeon RX 7900 XTX

AMD

CompatibleRuns Qwen3 30B-A3B Q4_K_M entirely in memory

Price not available

Availability unknown

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AMD Ryzen AI Max+ 395

Unified memory PC

ExcellentRuns Qwen3 30B-A3B Q4_K_M entirely in memory

Price not available

Availability unknown

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GeForce RTX 2080 Ti

Lowest memory tier

CompatibleRuns Qwen3 30B-A3B Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

How much VRAM does Qwen3 30B-A3B need?
About 19.9 GB at Q4_K_M with an 8K context, including the KV cache and runtime overhead. At Q8_0 it needs about 33.3 GB. A longer context adds more: about 3 GB of KV cache at 32K.
Can Qwen3 30B-A3B run on a Mac?
Yes on a Mac whose GPU can use at least 19.5 GB, e.g. M4 32 GB. macOS lets the GPU use about two thirds to three quarters of unified memory by default.
How fast is Qwen3 30B-A3B?
On a RTX 4090, we estimate 125–209 tok/s at Q4_K_M. This is an estimate from memory bandwidth (confidence low) until benchmarks are imported.