Model Comparison

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

Google

Gemini 1.5 Pro

Google

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.

Alibaba

QwQ-32B-Preview

Alibaba

QwQ-32B-Preview is a language model developed by Alibaba. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Google

Gemini 1.5 Pro

Google

2024-05-01

Alibaba

QwQ-32B-Preview

Alibaba

2024-11-28

7 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 1.5 Pro

Input:$2.50
Output:$10.00
Alibaba

QwQ-32B-Preview

$12.15 cheaper
Input:$0.15
Output:$0.20

Performance Metrics

Context window and performance specifications

Google

Gemini 1.5 Pro

Larger context
Max Context:2.1M
Alibaba

QwQ-32B-Preview

Max Context:65.5K
Parameters:32.5B

Average performance across 1 common benchmarks

Google

Gemini 1.5 Pro

Average Score:59.1%
Alibaba

QwQ-32B-Preview

+6.1%
Average Score:65.2%

Performance comparison across key benchmark categories

Google

Gemini 1.5 Pro

math
74.9%
code
+24.5%
74.5%
general
+11.3%
68.9%
Alibaba

QwQ-32B-Preview

math
+15.7%
90.6%
code
50.0%
general
57.6%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 1.5 Pro

2023-11-01

QwQ-32B-Preview

2024-11-28

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 1.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Alibaba

QwQ-32B-Preview

4 providers

Together

Throughput: 62.14 tok/s
Latency: 0.74ms

Hyperbolic

Throughput: 31.9 tok/s
Latency: 1.05ms

DeepInfra

Throughput: 76.04 tok/s
Latency: 0.44ms

Fireworks

Throughput: 99.15 tok/s
Latency: 0.53ms
Google

Gemini 1.5 Pro

Avg Score:59.1%
Providers:1
Alibaba

QwQ-32B-Preview

+6.1%
Avg Score:65.2%
Providers:4