Model Comparison

Phi-3.5-vision-instruct vs Qwen3 VL 8B Thinking

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Phi-3.5-vision-instruct outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 1 benchmark (AI2D).

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Wed Apr 29 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers

Wed Apr 29 2026 • llm-stats.com

Phi-3.5-vision-instruct

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

Qwen3 VL 8B Thinking

Input tokens$0.18

Output tokens$2.09

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

4.8B diff

Qwen3 VL 8B Thinking has 4.8B more parameters than Phi-3.5-vision-instruct, making it 114.3% larger.

Phi-3.5-vision-instruct

4.2Bparameters

Qwen3 VL 8B Thinking

9.0Bparameters

4.2B

Phi-3.5-vision-instruct

9.0B

Qwen3 VL 8B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 8B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 8B Thinking specifies output context (262,144 tokens).

Phi-3.5-vision-instruct

Input- tokens

Output- tokens

Qwen3 VL 8B Thinking

Input262,144 tokens

Output262,144 tokens

Wed Apr 29 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Phi-3.5-vision-instruct and Qwen3 VL 8B Thinking support multimodal inputs.

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

Phi-3.5-vision-instruct

Text

Images

Audio

Video

Qwen3 VL 8B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Phi-3.5-vision-instruct is licensed under MIT, while Qwen3 VL 8B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Phi-3.5-vision-instruct

MIT

Open weights

Qwen3 VL 8B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Phi-3.5-vision-instruct was released on 2024-08-23, while Qwen3 VL 8B Thinking was released on 2025-09-22.

Qwen3 VL 8B Thinking is 13 months newer than Phi-3.5-vision-instruct.

Phi-3.5-vision-instruct

Aug 23, 2024

1.7 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

7 months ago

1.1yr newer

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

Outputs Comparison

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Key Takeaways

Qwen3 VL 8B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Higher AI2D score (84.9% vs 78.1%)

Detailed Comparison

AI Model Comparison Table
Feature	Phi-3.5-vision-instruct	Qwen3 VL 8B Thinking

FAQ

Common questions about Phi-3.5-vision-instruct vs Qwen3 VL 8B Thinking

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Phi-3.5-vision-instruct is made by Microsoft and Qwen3 VL 8B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

Phi-3.5-vision-instruct scores ScienceQA: 91.3%, POPE: 86.1%, MMBench: 81.9%, ChartQA: 81.8%, AI2D: 78.1%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

Phi-3.5-vision-instruct supports an unknown number of tokens and Qwen3 VL 8B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Phi-3.5-vision-instruct is developed by Microsoft and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.

Phi-3.5-vision-instruct vs Qwen3 VL 8B Thinking

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

Phi-3.5-vision-instruct

Qwen3 VL 8B Thinking

License

Release Timeline

Knowledge Cutoff

Outputs Comparison

Key Takeaways

Phi-3.5-vision-instruct

Qwen3 VL 8B Thinking

Detailed Comparison

FAQ

Which is better, Phi-3.5-vision-instruct or Qwen3 VL 8B Thinking?

How does Phi-3.5-vision-instruct compare to Qwen3 VL 8B Thinking in benchmarks?

What are the context window sizes for Phi-3.5-vision-instruct and Qwen3 VL 8B Thinking?

What are the main differences between Phi-3.5-vision-instruct and Qwen3 VL 8B Thinking?

Who makes Phi-3.5-vision-instruct and Qwen3 VL 8B Thinking?