Model Comparison

Phi 4 vs Qwen3 VL 8B Thinking

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Phi 4 is 7.5x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Phi 4 outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 5 benchmarks (GPQA, IFEval, MMLU, MMLU-Pro, SimpleQA).

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Sun May 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Phi 4 costs less

For input processing, Phi 4 ($0.07/1M tokens) is 2.6x cheaper than Qwen3 VL 8B Thinking ($0.18/1M tokens).

For output processing, Phi 4 ($0.14/1M tokens) is 14.9x cheaper than Qwen3 VL 8B Thinking ($2.09/1M tokens).

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

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

Lowest available price from all providers

Sun May 17 2026 • llm-stats.com

Phi 4

Input tokens$0.07

Output tokens$0.14

Best providerDeepinfra

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

5.7B diff

Phi 4 has 5.7B more parameters than Qwen3 VL 8B Thinking, making it 63.3% larger.

Phi 4

14.7Bparameters

Qwen3 VL 8B Thinking

9.0Bparameters

14.7B

Phi 4

9.0B

Qwen3 VL 8B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 8B Thinking accepts 262,144 input tokens compared to Phi 4's 16,000 tokens. Qwen3 VL 8B Thinking can generate longer responses up to 262,144 tokens, while Phi 4 is limited to 16,000 tokens.

Phi 4

Input16,000 tokens

Output16,000 tokens

Qwen3 VL 8B Thinking

Input262,144 tokens

Output262,144 tokens

Sun May 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 8B Thinking supports multimodal inputs, whereas Phi 4 does not.

Qwen3 VL 8B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Phi 4

Text

Images

Audio

Video

Qwen3 VL 8B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Phi 4 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 4

MIT

Open weights

Qwen3 VL 8B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Phi 4 was released on 2024-12-12, while Qwen3 VL 8B Thinking was released on 2025-09-22.

Qwen3 VL 8B Thinking is 9 months newer than Phi 4.

Phi 4

Dec 12, 2024

1.4 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

7 months ago

9mo newer

Knowledge Cutoff

When training data ends

Phi 4 has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 8B Thinking's cutoff date is not specified.

We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3 VL 8B Thinking's cutoff date.

Phi 4

Jun 2024

Qwen3 VL 8B Thinking

—

Provider Availability

Phi 4 is available from DeepInfra. Qwen3 VL 8B Thinking is available from DeepInfra.

Phi 4

Deepinfra

Input Price:Input: $0.07/1MOutput Price:Output: $0.14/1M

Qwen3 VL 8B Thinking

Deepinfra

Input Price:Input: $0.18/1MOutput Price:Output: $2.09/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Phi 4

View details

Microsoft

Less expensive input tokens

Less expensive output tokens

Qwen3 VL 8B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Supports multimodal inputs

Higher GPQA score (69.9% vs 56.1%)

Higher IFEval score (83.2% vs 63.0%)

Higher MMLU score (85.2% vs 84.8%)

Higher MMLU-Pro score (77.3% vs 70.4%)

Higher SimpleQA score (49.6% vs 3.0%)

Detailed Comparison

AI Model Comparison Table
Feature	Phi 4	Qwen3 VL 8B Thinking

FAQ

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

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

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Phi 4 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.

How does Phi 4 compare to Qwen3 VL 8B Thinking in benchmarks?

Phi 4 scores MMLU: 84.8%, HumanEval+: 82.8%, HumanEval: 82.6%, MGSM: 80.6%, MATH: 80.4%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

Is Phi 4 cheaper than Qwen3 VL 8B Thinking?

Phi 4 is 2.6x cheaper for input tokens. Phi 4 costs $0.07/M input and $0.14/M output via deepinfra. Qwen3 VL 8B Thinking costs $0.18/M input and $2.09/M output via deepinfra.

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

Phi 4 supports 16K 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.

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

Key differences include context window (16K vs 262K), input pricing ($0.07 vs $0.18/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Phi 4 and Qwen3 VL 8B Thinking?

Phi 4 is developed by Microsoft and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.