Model Comparison

Grok-4 Fast Non-Reasoning vs Qwen2.5 VL 7B Instruct

Comparing Grok-4 Fast Non-Reasoning and Qwen2.5 VL 7B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Grok-4 Fast Non-Reasoning and Qwen2.5 VL 7B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Grok-4 Fast Non-Reasoning specifies input context (2,000,000 tokens). Only Grok-4 Fast Non-Reasoning specifies output context (30,000 tokens).

Grok-4 Fast Non-Reasoning

Input2,000,000 tokens

Output30,000 tokens

Qwen2.5 VL 7B Instruct

Input- tokens

Output- tokens

Mon May 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Grok-4 Fast Non-Reasoning and Qwen2.5 VL 7B Instruct support multimodal inputs.

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

Grok-4 Fast Non-Reasoning

Text

Images

Audio

Video

Qwen2.5 VL 7B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

Grok-4 Fast Non-Reasoning is licensed under a proprietary license, while Qwen2.5 VL 7B Instruct uses Apache 2.0.

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

Grok-4 Fast Non-Reasoning

Proprietary

Closed source

Qwen2.5 VL 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Grok-4 Fast Non-Reasoning was released on 2025-08-28, while Qwen2.5 VL 7B Instruct was released on 2025-01-26.

Grok-4 Fast Non-Reasoning is 7 months newer than Qwen2.5 VL 7B Instruct.

Grok-4 Fast Non-Reasoning

Aug 28, 2025

9 months ago

7mo newer

Qwen2.5 VL 7B Instruct

Jan 26, 2025

1.3 years 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

Outputs Comparison

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Key Takeaways

Grok-4 Fast Non-Reasoning

View details

xAI

Larger context window (2,000,000 tokens)

Qwen2.5 VL 7B Instruct

View details

Alibaba Cloud / Qwen Team

Has open weights

Detailed Comparison

AI Model Comparison Table
Feature	Grok-4 Fast Non-Reasoning	Qwen2.5 VL 7B Instruct

FAQ

Common questions about Grok-4 Fast Non-Reasoning vs Qwen2.5 VL 7B Instruct.

Which is better, Grok-4 Fast Non-Reasoning or Qwen2.5 VL 7B Instruct?

Grok-4 Fast Non-Reasoning (xAI) and Qwen2.5 VL 7B Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Grok-4 Fast Non-Reasoning compare to Qwen2.5 VL 7B Instruct in benchmarks?

Qwen2.5 VL 7B Instruct scores DocVQA: 95.7%, Android Control Low_EM: 91.4%, MobileMiniWob++_SR: 91.4%, ChartQA: 87.3%, OCRBench: 86.4%.

What are the context window sizes for Grok-4 Fast Non-Reasoning and Qwen2.5 VL 7B Instruct?

Grok-4 Fast Non-Reasoning supports 2.0M tokens and Qwen2.5 VL 7B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Grok-4 Fast Non-Reasoning and Qwen2.5 VL 7B Instruct?

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

Who makes Grok-4 Fast Non-Reasoning and Qwen2.5 VL 7B Instruct?

Grok-4 Fast Non-Reasoning is developed by xAI and Qwen2.5 VL 7B Instruct is developed by Alibaba Cloud / Qwen Team.