Qwen3 VL 4B Instruct vs Qwen3 VL 4B Thinking
Qwen3 VL 4B Instruct and Qwen3 VL 4B Thinking are closely matched at 10.2 and 12.5 on the LLM Stats Score. Qwen3 VL 4B Instruct is 1.4x cheaper per token.
Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 4B Instruct and Qwen3 VL 4B Thinking are closely matched on the overall LLM Stats Score at 10.2 and 12.5.
In the 44 individual benchmarks reported for both models, Qwen3 VL 4B Thinking wins 34; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 VL 4B Instruct is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Qwen3 VL 4B Instruct
- cost matters — it's about 1.4x cheaper per token
Choose Qwen3 VL 4B Thinking
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 34 of 44 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
1 more shared indexes
Individual benchmarks
45 reported for Qwen3 VL 4B Instruct · 48 for Qwen3 VL 4B Thinking
Qwen3 VL 4B Instruct outperforms in 10 benchmarks (BLINK, CC-OCR, DocVQAtest, LVBench, OCRBench, OCRBench-V2 (en), OCRBench-V2 (zh), ODinW, ScreenSpot, ScreenSpot Pro), while Qwen3 VL 4B Thinking is better at 34 benchmarks (AI2D, AIME 2025, BFCL-v3, CharadesSTA, CharXiv-D, CharXiv-R, ERQA, Hallusion Bench, HMMT25, IFEval, Include, InfoVQAtest, LiveBench 20241125, LiveCodeBench v6, MathVision, MathVista-Mini, MLVU-M, MMBench-V1.1, MMLU, MMLU-Pro, MMLU-ProX, MMLU-Redux, MM-MT-Bench, MMMU-Pro, MMMU (val), MMStar, MuirBench, MVBench, OSWorld, PolyMATH, RealWorldQA, SuperGPQA, VideoMMMU, WritingBench).
Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3 VL 4B Instruct ($0.10/1M tokens) costs the same as Qwen3 VL 4B Thinking ($0.10/1M tokens).
For output processing, Qwen3 VL 4B Instruct ($0.60/1M tokens) is 1.7x cheaper than Qwen3 VL 4B Thinking ($1.00/1M tokens).
In conclusion, Qwen3 VL 4B Thinking is more expensive than Qwen3 VL 4B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 VL 4B Thinking has 0.0B more parameters than Qwen3 VL 4B Instruct, making it 0.0% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 262,144 tokens. Both models can generate responses up to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
Both Qwen3 VL 4B Instruct and Qwen3 VL 4B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3 VL 4B Instruct
Qwen3 VL 4B Thinking
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Both models were released on 2025-09-22.
They likely represent similar generations of model development.
Sep 22, 2025
1.1 years ago
Sep 22, 2025
1.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Qwen3 VL 4B Instruct is available from DeepInfra. Qwen3 VL 4B Thinking is available from DeepInfra.
Qwen3 VL 4B Instruct
Qwen3 VL 4B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen3 VL 4B Instruct and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3 VL 4B Instruct vs Qwen3 VL 4B Thinking.