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Gemini 1.5 Pro vs Qwen3-235B-A22B-Thinking-2507
Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B-Thinking-2507 leads with 1.3% higher average benchmark score. Gemini 1.5 Pro offers 1.7M more tokens in context window than Qwen3-235B-A22B-Thinking-2507. Qwen3-235B-A22B-Thinking-2507 is $9.20 cheaper per million tokens. Gemini 1.5 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Google's latest advancement in AI technology.
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Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507 is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 69.2% across 25 benchmarks. It excels particularly in MMLU-Redux (93.8%), AIME 2025 (92.3%), WritingBench (88.3%). It supports a 387K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
1 year newer
Gemini 1.5 Pro
2024-05-01
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
2025-07-25
Pricing Comparison
Cost per million tokens (USD)
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Gemini 1.5 Pro
Input:$2.50
Output:$10.00
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Qwen3-235B-A22B-Thinking-2507
Input:$0.30
Output:$3.00($9.20 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 46 common benchmarks
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Gemini 1.5 Pro
Average Score:36.3%
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Qwen3-235B-A22B-Thinking-2507
Average Score:37.6%(+1.3%)
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Knowledge Cutoff
Training data recency comparison
Gemini 1.5 Pro
2023-11-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 1.5 Pro
1 providers
Throughput: 85 tok/s
Latency: 0.7ms
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Qwen3-235B-A22B-Thinking-2507
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Gemini 1.5 Pro
Avg Score:36.3%
Providers:1
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Qwen3-235B-A22B-Thinking-2507
Avg Score:37.6%(+1.3%)
Providers:1