Qwen3-4B-Instruct-2507
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
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Deep dive
Notes, sources, and the full write-up
Qwen3-4B-Instruct-2507
Qwen3-4B-Instruct-2507 is a 4B-parameter apache-2.0 model from Qwen. At Q4_K_M it needs roughly 2 GB of VRAM, placing it in the cpu hardware tier.
Specifications
| Spec | Value |
|---|---|
| Parameters | 4B |
| Context length | 262K tokens |
| License | apache-2.0 |
| Modalities | text |
| Released | 2025-08-05 |
| Weights | Qwen/Qwen3-4B-Instruct-2507 |
VRAM requirements
| Quant | VRAM | Runs on |
|---|---|---|
| Q4_K_M | ~2 GB | RTX 4060, RTX 3060 8GB |
| Q5_K_M | ~3 GB | RTX 4060, RTX 3060 8GB |
| Q8_0 | ~4 GB | RTX 4060, RTX 3060 8GB |
| FP16 | ~8 GB | RTX 4060, RTX 3060 8GB |
VRAM is estimated from parameter count; MoE models still need all weights resident.
How to run
vLLM:
vllm serve Qwen/Qwen3-4B-Instruct-2507Popularity
Qwen3-4B-Instruct-2507 has 4,833,125 downloads in the last month on HuggingFace and 869 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Qwen3-4B-Instruct-2507 need?
Qwen3-4B-Instruct-2507 with 4B parameters needs approximately 2 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Qwen3-4B-Instruct-2507 better than other Qwen models?
Qwen3-4B-Instruct-2507 has 4B parameters with 262,144 context - a strong choice for general use.
What license is Qwen3-4B-Instruct-2507 under?
Qwen3-4B-Instruct-2507 is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs Qwen3-4B-Instruct-2507 well?
With 4B parameters, Qwen3-4B-Instruct-2507 requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Qwen3-4B-Instruct-2507?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~3 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Qwen3-4B-Instruct-2507's context window handle?
Qwen3-4B-Instruct-2507 supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Qwen3-4B-Instruct-2507?
Qwen3-4B-Instruct-2507 competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec
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