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Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 2.5 Pro

Google

Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 67.0% across 24 benchmarks. It excels particularly in MMLU-Redux (90.9%), MultiPL-E (87.8%), IFEval (87.6%). It supports a 131K 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.

Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

Alibaba Cloud / Qwen Team

2025-01-10

Google

Gemini 2.5 Pro

Google

2025-05-20

4 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.5 Pro

Input:$1.25
Output:$10.00
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

$9.60 cheaper
Input:$0.15
Output:$1.50

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

Max Context:131.1K
Parameters:80.0B

Average performance across 2 common benchmarks

Google

Gemini 2.5 Pro

+18.4%
Average Score:79.8%
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

Average Score:61.3%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

factuality
50.8%
math
+37.1%
83.0%
general
74.1%
code
+2.1%
72.6%
reasoning
4.9%
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

factuality
+40.1%
90.9%
math
45.9%
general
+1.7%
75.8%
code
70.5%
reasoning
+53.9%
58.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.5 Pro

2025-01-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.5 Pro

2 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms

ZeroEval

Throughput: 85 tok/s
Latency: 0.7ms
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

1 providers

Novita

Google

Gemini 2.5 Pro

+18.4%
Avg Score:79.8%
Providers:2
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

Avg Score:61.3%
Providers:1