Model Comparison

Qwen3 VL 4B Thinking vs Qwen3 VL 8B InstructWhich is better in 2026?

Qwen3 VL 4B Thinking has a slight edge in benchmark performance. Qwen3 VL 8B Instruct is 1.8x cheaper per token.

Verdict: Qwen3 VL 4B Thinking vs Qwen3 VL 8B Instruct — which is better?

Qwen3 VL 4B Thinking (by Alibaba Cloud / Qwen Team) and Qwen3 VL 8B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Qwen3 VL 4B Thinking outperforms in 26 benchmarks (AIME 2025, BFCL-v3, CharadesSTA, CharXiv-D, CharXiv-R, ERQA, Hallusion Bench, HMMT25, LiveBench 20241125, LiveCodeBench v6, MathVision, MathVista-Mini, MMBench-V1.1, MMLU, MMLU-Pro, MMLU-Redux, MMMU-Pro, MMMU (val), MMStar, MuirBench, MVBench, PolyMATH, RealWorldQA, SuperGPQA, VideoMMMU, WritingBench), while Qwen3 VL 8B Instruct is better at 18 benchmarks (AI2D, BLINK, CC-OCR, DocVQAtest, IFEval, Include, InfoVQAtest, LVBench, MLVU-M, MMLU-ProX, Multi-IF, OCRBench, OCRBench-V2 (en), OCRBench-V2 (zh), ODinW, OSWorld, ScreenSpot, ScreenSpot Pro). Qwen3 VL 4B Thinking has a slight edge in benchmark performance.

On price, Qwen3 VL 8B Instruct is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3 VL 4B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Qwen3 VL 4B Thinking if…

  • you want the strongest raw capability — it leads on 26 of 45 shared benchmarks
  • you process long inputs — it offers a 262,144 token context window

Choose Qwen3 VL 8B Instruct if…

  • cost matters — it's about 1.8x cheaper per token
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Performance Benchmarks

Comparative analysis across standard metrics

45 benchmarks

Qwen3 VL 4B Thinking outperforms in 26 benchmarks (AIME 2025, BFCL-v3, CharadesSTA, CharXiv-D, CharXiv-R, ERQA, Hallusion Bench, HMMT25, LiveBench 20241125, LiveCodeBench v6, MathVision, MathVista-Mini, MMBench-V1.1, MMLU, MMLU-Pro, MMLU-Redux, MMMU-Pro, MMMU (val), MMStar, MuirBench, MVBench, PolyMATH, RealWorldQA, SuperGPQA, VideoMMMU, WritingBench), while Qwen3 VL 8B Instruct is better at 18 benchmarks (AI2D, BLINK, CC-OCR, DocVQAtest, IFEval, Include, InfoVQAtest, LVBench, MLVU-M, MMLU-ProX, Multi-IF, OCRBench, OCRBench-V2 (en), OCRBench-V2 (zh), ODinW, OSWorld, ScreenSpot, ScreenSpot Pro).

Qwen3 VL 4B Thinking has a slight edge in benchmark performance.

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 8B Instruct costs less

For input processing, Qwen3 VL 4B Thinking ($0.10/1M tokens) is 1.3x more expensive than Qwen3 VL 8B Instruct ($0.08/1M tokens).

For output processing, Qwen3 VL 4B Thinking ($1.00/1M tokens) is 2.0x more expensive than Qwen3 VL 8B Instruct ($0.50/1M tokens).

In conclusion, Qwen3 VL 4B Thinking is more expensive than Qwen3 VL 8B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input tokens$0.10
Output tokens$1.00
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
Input tokens$0.08
Output tokens$0.50
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

5.0B diff

Qwen3 VL 8B Instruct has 5.0B more parameters than Qwen3 VL 4B Thinking, making it 125.0% larger.

Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
9.0Bparameters
4.0B
Qwen3 VL 4B Thinking
9.0B
Qwen3 VL 8B Instruct

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to Qwen3 VL 8B Instruct's 131,072 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while Qwen3 VL 8B Instruct is limited to 32,768 tokens.

Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
Input131,072 tokens
Output32,768 tokens
Sat Jun 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen3 VL 4B Thinking and Qwen3 VL 8B Instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

Qwen3 VL 8B Instruct

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 Thinking

Apache 2.0

Open weights

Qwen3 VL 8B Instruct

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 Thinking

Sep 22, 2025

8 months ago

Qwen3 VL 8B Instruct

Sep 22, 2025

8 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 Thinking is available from DeepInfra. Qwen3 VL 8B Instruct is available from Novita, DeepInfra.

Qwen3 VL 4B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M

Qwen3 VL 8B Instruct

novita logo
Novita
Input Price:Input: $0.08/1MOutput Price:Output: $0.50/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.69/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Alibaba Cloud / Qwen Team

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Higher AIME 2025 score (74.5% vs 45.9%)
Higher BFCL-v3 score (67.3% vs 66.3%)
Higher CharadesSTA score (59.0% vs 56.0%)
Higher CharXiv-D score (83.9% vs 83.0%)
Higher CharXiv-R score (50.3% vs 46.4%)
Higher ERQA score (47.3% vs 45.8%)
Higher Hallusion Bench score (64.1% vs 61.1%)
Higher HMMT25 score (53.1% vs 32.5%)
Higher LiveBench 20241125 score (68.4% vs 62.0%)
Higher LiveCodeBench v6 score (51.3% vs 39.3%)
Higher MathVision score (60.0% vs 53.9%)
Higher MathVista-Mini score (79.5% vs 77.2%)
Higher MMBench-V1.1 score (86.7% vs 85.0%)
Higher MMLU score (81.5% vs 80.7%)
Higher MMLU-Pro score (73.6% vs 71.6%)
Higher MMLU-Redux score (86.0% vs 84.9%)
Higher MMMU-Pro score (57.0% vs 55.9%)
Higher MMMU (val) score (70.8% vs 69.6%)
Higher MMStar score (73.2% vs 70.9%)
Higher MuirBench score (75.0% vs 64.4%)
Higher MVBench score (69.3% vs 68.7%)
Higher PolyMATH score (44.6% vs 30.4%)
Higher RealWorldQA score (73.2% vs 71.5%)
Higher SuperGPQA score (46.8% vs 44.5%)
Higher VideoMMMU score (69.4% vs 65.3%)
Higher WritingBench score (84.0% vs 83.1%)
Alibaba Cloud / Qwen Team

Qwen3 VL 8B Instruct

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens
Less expensive output tokens
Higher AI2D score (85.7% vs 84.9%)
Higher BLINK score (69.1% vs 63.4%)
Higher CC-OCR score (79.9% vs 73.8%)
Higher DocVQAtest score (96.1% vs 94.2%)
Higher IFEval score (83.7% vs 82.6%)
Higher Include score (67.0% vs 64.6%)
Higher InfoVQAtest score (83.1% vs 83.0%)
Higher LVBench score (58.0% vs 53.5%)
Higher MLVU-M score (78.1% vs 75.7%)
Higher MMLU-ProX score (65.4% vs 65.0%)
Higher Multi-IF score (75.1% vs 73.6%)
Higher OCRBench score (89.6% vs 80.8%)
Higher OCRBench-V2 (en) score (65.4% vs 61.8%)
Higher OCRBench-V2 (zh) score (61.2% vs 55.8%)
Higher ODinW score (44.7% vs 39.4%)
Higher OSWorld score (33.9% vs 31.4%)
Higher ScreenSpot score (94.4% vs 92.9%)
Higher ScreenSpot Pro score (54.6% vs 49.2%)

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct

FAQ

Common questions about Qwen3 VL 4B Thinking vs Qwen3 VL 8B Instruct.

Which is better, Qwen3 VL 4B Thinking or Qwen3 VL 8B Instruct?

Qwen3 VL 4B Thinking has a slight edge in benchmark performance. Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team and Qwen3 VL 8B Instruct 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 Thinking compare to Qwen3 VL 8B Instruct in benchmarks?

Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%. Qwen3 VL 8B Instruct scores DocVQAtest: 96.1%, ScreenSpot: 94.4%, OCRBench: 89.6%, AI2D: 85.7%, MMBench-V1.1: 85.0%.

Is Qwen3 VL 4B Thinking cheaper than Qwen3 VL 8B Instruct?

Qwen3 VL 8B Instruct is 1.3x cheaper for input tokens. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output via deepinfra. Qwen3 VL 8B Instruct costs $0.08/M input and $0.50/M output via novita.

What are the context window sizes for Qwen3 VL 4B Thinking and Qwen3 VL 8B Instruct?

Qwen3 VL 4B Thinking supports 262K tokens and Qwen3 VL 8B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen3 VL 4B Thinking and Qwen3 VL 8B Instruct?

Key differences include context window (262K vs 131K), input pricing ($0.10 vs $0.08/M). See the full comparison above for benchmark-by-benchmark results.

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