Gemini 1.5 Pro
Multimodal
Zero-eval
#1XSTest
#1WMT23
#1FunctionalMATH
+8 more
by Google
+
+
+
+
About
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.
+
+
+
+
Pricing Range
Input (per 1M)$2.50 -$2.50
Output (per 1M)$10.00 -$10.00
Providers1
+
+
+
+
Timeline
AnnouncedMay 1, 2024
ReleasedMay 1, 2024
Knowledge CutoffNov 1, 2023
+
+
+
+
Specifications
Capabilities
Multimodal
+
+
+
+
License & Family
License
Proprietary
Performance Overview
Performance metrics and category breakdown
Overall Performance
23 benchmarks
Average Score
72.6%
Best Score
98.8%
High Performers (80%+)
10Performance Metrics
Max Context Window
2.1MAvg Throughput
85.0 tok/sAvg Latency
1ms+
+
+
+
All Benchmark Results for Gemini 1.5 Pro
Complete list of benchmark scores with detailed information
| XSTest | text | 0.99 | 98.8% | Self-reported | |
| HellaSwag | text | 0.93 | 93.3% | Self-reported | |
| GSM8k | text | 0.91 | 90.8% | Self-reported | |
| BIG-Bench Hard | text | 0.89 | 89.2% | Self-reported | |
| MGSM | text | 0.88 | 87.5% | Self-reported | |
| MATH | text | 0.86 | 86.5% | Self-reported | |
| MMLU | text | 0.86 | 85.9% | Self-reported | |
| Natural2Code | text | 0.85 | 85.4% | Self-reported | |
| HumanEval | text | 0.84 | 84.1% | Self-reported | |
| MRCR | text | 0.83 | 82.6% | Self-reported |
Showing 1 to 10 of 23 benchmarks