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LLM ComparisonGemini 2.5 Pro ExperimentalQwen-Max

Gemini 2.5 Pro Experimental vs Qwen-Max

Compare Gemini 2.5 Pro Experimental and Qwen-Max. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGemini 2.5 Pro ExperimentalQwen-Max
ProviderGoogleAlibaba Cloud
Model Typetexttext
Context Window1,048,576 tokens32,768 tokens
Input Cost
$1.50/ 1M tokens
$1.60/ 1M tokens
Output Cost
$6.00/ 1M tokens
$6.40/ 1M tokens

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Strengths & Best Use Cases

Gemini 2.5 Pro Experimental

Google

1. State-of-the-art reasoning performance

  • #1 on LMArena human preference leaderboard.
  • Excels at advanced reasoning benchmarks like GPQA and AIME 2025.
  • Achieves 18.8% on Humanity's Last Exam (no tools), representing frontier human-level reasoning.

2. New “thinking model” architecture

  • Built with explicit reasoning steps internally before responding.
  • Handles complex, multi-stage logic with higher accuracy and fewer hallucinations.

3. Elite science and mathematics capabilities

  • Leads in math and science tasks across industry benchmarks.
  • High performance without costly inference tricks like majority voting.

4. Exceptional coding abilities

  • Major leap over Gemini 2.0 in coding performance.
  • 63.8% on SWE-Bench Verified with custom agent setup.
  • Strong at code transformation, debugging, and building agentic apps.
  • Capable of generating full applications (e.g., a playable video game) from a single-line prompt.

5. Massive multimodal context

  • Ships with a 1,000,000 token window (2M coming soon).
  • Handles entire documents, datasets, video sequences, audio files, and large codebases.
  • Maintains strong performance even at extreme context lengths.

6. Native multimodality across all inputs

  • Understands and reasons over text, images, audio, video, and code.
  • Designed for real-world, multi-source problem-solving and agent workflows.

7. Consistent high-quality outputs

  • Improved post-training results in more accurate, coherent, and stylistically strong responses.
  • Higher reliability across complex workloads.

8. Early availability for developers

  • Available today in Google AI Studio for experimentation.
  • Coming soon to Vertex AI with higher rate limits and production-ready access.

Qwen-Max

Alibaba Cloud

1. Strong general-purpose reasoning

  • Great for coding, analysis, creation, and multi-step tasks.

2. Stable commercial-grade model

  • Predictable output quality and long-term stability.

3. Supports batch operations

  • Batch inference is 50% cheaper.

4. Good for production agents

  • Reliable instruction following and structured output.

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