What GPU do I need to run Qwen/Qwen3-4B-Instruct-2507?
4.0B parameters, published in BF16. View on Hugging Face
Set up Qwen3-4B-Instruct-2507Qwen3-4B-Instruct-2507 is published by Qwen on Hugging Face, with 3,463,487 downloads and 945 likes to date. It's a Qwen3ForCausalLM model built for text-generation, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 7.5 GB | 9.0 GB | RTX 5060 Ti | 1 | $0.110/hr |
| FP8 (quantized) | 3.7 GB | 4.5 GB | RTX 5060 Ti | 1 | $0.110/hr |
| INT4 (quantized) | 1.9 GB | 2.2 GB | RTX 5060 Ti | 1 | $0.110/hr |
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run Qwen3-4B-Instruct-2507 at its published (BF16) precision: 1× RTX 5060 Ti, at $0.110/hr per GPU ($0.110/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Qwen3-4B-Instruct-2507: common questions
Does Qwen3-4B-Instruct-2507 fit on a 12 GB GPU?
Yes. At BF16 it needs 9.0 GB of VRAM, so a 12 GB card holds it with 3.0 GB to spare. An 8 GB card is not enough for it at BF16.
What is the least VRAM Qwen3-4B-Instruct-2507 can run in?
2.2 GB, at INT4 (quantized), which fits a 6 GB card, against 9.0 GB at BF16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More Qwen3 models
- Qwen3-4B (4.0B, BF16)
- Qwen3-4B-Base (4.0B, BF16)
- Qwen3-4B-Thinking-2507 (4.0B, BF16)
- Qwen3-4B-Instruct-2507 (4.0B, BF16)
- Qwen3-Reranker-4B (4.0B, BF16)
Related reading: H100 pricing and specs, The best GPUs for AI, ranked, and Best GPU for LLM inference.
