Model Comparison

Qwen3 VL 4B Instruct vs Qwen3 VL 4B Thinking

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks. Qwen3 VL 4B Instruct is 1.4x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

44 benchmarks

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.

Mon May 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 4B Instruct costs less

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

Lowest available price from all providers

Mon May 18 2026 • llm-stats.com

Qwen3 VL 4B Instruct

Input tokens$0.10

Output tokens$0.60

Best providerDeepinfra

Qwen3 VL 4B Thinking

Input tokens$0.10

Output tokens$1.00

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

0.0M diff

Qwen3 VL 4B Thinking has 0.0B more parameters than Qwen3 VL 4B Instruct, making it 0.0% larger.

Qwen3 VL 4B Instruct

4.0Bparameters

Qwen3 VL 4B Thinking

4.0Bparameters

4.0B

Qwen3 VL 4B Instruct

4.0B

Qwen3 VL 4B Thinking

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.

Qwen3 VL 4B Instruct

Input262,144 tokens

Output262,144 tokens

Qwen3 VL 4B Thinking

Input262,144 tokens

Output262,144 tokens

Mon May 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Text

Images

Audio

Video

Qwen3 VL 4B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3 VL 4B Instruct

Apache 2.0

Open weights

Qwen3 VL 4B Thinking

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.

Qwen3 VL 4B Instruct

Sep 22, 2025

7 months ago

Qwen3 VL 4B Thinking

Sep 22, 2025

7 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Qwen3 VL 4B Instruct is available from DeepInfra. Qwen3 VL 4B Thinking is available from DeepInfra.

Qwen3 VL 4B Instruct

Deepinfra

Input Price:Input: $0.10/1MOutput Price:Output: $0.60/1M

Qwen3 VL 4B Thinking

Deepinfra

Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Qwen3 VL 4B Instruct

View details

Alibaba Cloud / Qwen Team

Less expensive output tokens

Higher BLINK score (65.8% vs 63.4%)

Higher CC-OCR score (76.2% vs 73.8%)

Higher DocVQAtest score (95.3% vs 94.2%)

Higher LVBench score (56.2% vs 53.5%)

Higher OCRBench score (88.1% vs 80.8%)

Higher OCRBench-V2 (en) score (63.7% vs 61.8%)

Higher OCRBench-V2 (zh) score (57.6% vs 55.8%)

Higher ODinW score (48.2% vs 39.4%)

Higher ScreenSpot score (94.0% vs 92.9%)

Higher ScreenSpot Pro score (59.5% vs 49.2%)

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Higher AI2D score (84.9% vs 84.1%)

Higher AIME 2025 score (74.5% vs 46.6%)

Higher BFCL-v3 score (67.3% vs 63.3%)

Higher CharadesSTA score (59.0% vs 55.5%)

Higher CharXiv-D score (83.9% vs 76.2%)

Higher CharXiv-R score (50.3% vs 39.7%)

Higher ERQA score (47.3% vs 41.3%)

Higher Hallusion Bench score (64.1% vs 57.6%)

Higher HMMT25 score (53.1% vs 30.7%)

Higher IFEval score (82.6% vs 82.3%)

Higher Include score (64.6% vs 61.4%)

Higher InfoVQAtest score (83.0% vs 80.3%)

Higher LiveBench 20241125 score (68.4% vs 60.9%)

Higher LiveCodeBench v6 score (51.3% vs 37.9%)

Higher MathVision score (60.0% vs 51.6%)

Higher MathVista-Mini score (79.5% vs 73.7%)

Higher MLVU-M score (75.7% vs 75.3%)

Higher MMBench-V1.1 score (86.7% vs 85.1%)

Higher MMLU score (81.5% vs 77.2%)

Higher MMLU-Pro score (73.6% vs 67.1%)

Higher MMLU-ProX score (65.0% vs 59.4%)

Higher MMLU-Redux score (86.0% vs 81.5%)

Higher MM-MT-Bench score (7.7% vs 7.5%)

Higher MMMU-Pro score (57.0% vs 53.2%)

Higher MMMU (val) score (70.8% vs 67.4%)

Higher MMStar score (73.2% vs 69.8%)

Higher MuirBench score (75.0% vs 63.8%)

Higher MVBench score (69.3% vs 68.9%)

Higher OSWorld score (31.4% vs 26.2%)

Higher PolyMATH score (44.6% vs 28.8%)

Higher RealWorldQA score (73.2% vs 70.9%)

Higher SuperGPQA score (46.8% vs 40.3%)

Higher VideoMMMU score (69.4% vs 56.2%)

Higher WritingBench score (84.0% vs 82.5%)

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3 VL 4B Instruct	Qwen3 VL 4B Thinking

FAQ

Common questions about Qwen3 VL 4B Instruct vs Qwen3 VL 4B Thinking.

Which is better, Qwen3 VL 4B Instruct or Qwen3 VL 4B Thinking?

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks. Qwen3 VL 4B Instruct is made by Alibaba Cloud / Qwen Team and Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen3 VL 4B Instruct compare to Qwen3 VL 4B Thinking in benchmarks?

Qwen3 VL 4B Instruct scores DocVQAtest: 95.3%, ScreenSpot: 94.0%, OCRBench: 88.1%, MMBench-V1.1: 85.1%, AI2D: 84.1%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

Is Qwen3 VL 4B Instruct cheaper than Qwen3 VL 4B Thinking?

Both models cost $0.10 per million input tokens.

What are the context window sizes for Qwen3 VL 4B Instruct and Qwen3 VL 4B Thinking?

Qwen3 VL 4B Instruct supports 262K tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.