Qwen3.5 4B
Qwenapache-2.0textvision

Qwen3.5 4B

Updated Jul 23, 2026
Parameters
4.7B
Context
262,144
License
apache-2.0
Updated
Jul 23, 2026

Intelligence benchmarks

Artificial Analysis indexes - compared with the best open and proprietary models

Intelligence

20.1

AA Index

Coding

22.6

AA Index

Intelligence Index - Qwen3.5 4B vs. the field

Best open-weight models (you can run locally) and leading proprietary models for context.

Claude Fable 5 (with fallback)
59.9
closed
GPT-5.6 Sol (max)
58.9
closed
Kimi K3
57.1
closed
Claude Opus 4.8 (max)
55.7
closed
GPT-5.6 Terra (max)
55
closed
GLM-5.2
51.1
open
MiniMax-M3
44.4
open
Qwen3.5 4B
20.1
open

Coding Index comparison

GPT-5.6 Sol (xhigh)
78.3
closed
GPT-5.6 Terra (max)
76.7
closed
Claude Fable 5 (with fallback)
76.5
closed
Kimi K3
76.2
closed
Claude Opus 4.8 (max)
74.3
closed
GLM-5.2
68.8
open
Kimi K2.7 Code
60.8
open
Qwen3.5 4B
22.6
open

Benchmark data from Artificial Analysis · updated 2026-07-23.

Standard benchmarks

Performance across standard evaluations

BenchmarkScore
GPQA77.1

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at FP16
4 of 4 quantizations fit Qwen3.5 4B with real runtime overhead.
Q4_K_M
3 GB
Q5_K_M
3 GB
Q8_0
5 GB
FP16
9 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve Qwen/Qwen3.5-4B

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

Qwen3.5 4B is a 4.7B-parameter apache-2.0 model from Alibaba. It scores 27.1 on the Artificial Analysis Intelligence Index (coding 17.5). At Q4_K_M it needs roughly 3 GB of VRAM, placing it in the CPU / ≤4 GB hardware tier.

Benchmarks

Artificial Analysis Intelligence Index - Qwen3.5 4B vs. leading closed models:

ModelIntelligenceCodingGPQA
Qwen3.5 4B27.117.577.1
GPT-5.5 (xhigh)60.259.193.5
Claude Opus 4.8 (max)61.456.792
Gemini 3.1 Pro Preview57.255.594.1
Grok 4.3 (high)53.24190.1

Source: Artificial Analysis (2026-06-07).

Popularity

Qwen3.5 4B has 9,934,423 downloads in the last month on HuggingFace and 612 likes.

Frequently asked

Quick answers to common questions

How much VRAM does Qwen3.5 4B need?

Qwen3.5 4B with 4.7B parameters needs approximately 3 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is Qwen3.5 4B better than other Qwen models?

Qwen3.5 4B has 4.7B parameters with 262,144 context - a strong choice for general use.

What license is Qwen3.5 4B under?

Qwen3.5 4B is released under the apache-2.0 license, making it suitable for most commercial and personal projects.

What hardware runs Qwen3.5 4B well?

With 4.7B parameters, Qwen3.5 4B 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 Qwen3.5 4B?

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 Qwen3.5 4B's context window handle?

Qwen3.5 4B 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 Qwen3.5 4B?

Qwen3.5 4B 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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