Gemma 3 27B
Multimodal
Zero-eval
#1MMMU (val)
#1WMT24++
#1BIG-Bench Extra Hard
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by Google
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About
Gemma 3 27B is a multimodal language model developed by Google. It achieves strong performance with an average score of 65.4% across 26 benchmarks. It excels particularly in GSM8k (95.9%), IFEval (90.4%), MATH (89.0%). It supports a 262K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.
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Pricing Range
Input (per 1M)$0.10 -$0.11
Output (per 1M)$0.20 -$0.20
Providers2
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Timeline
AnnouncedMar 12, 2025
ReleasedMar 12, 2025
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Specifications
Training Tokens14.0T
Capabilities
Multimodal
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License & Family
License
Gemma
Performance Overview
Performance metrics and category breakdown
Overall Performance
26 benchmarks
Average Score
65.4%
Best Score
95.9%
High Performers (80%+)
8Performance Metrics
Max Context Window
262.1KAvg Throughput
33.0 tok/sAvg Latency
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All Benchmark Results for Gemma 3 27B
Complete list of benchmark scores with detailed information
| GSM8k | text | 0.96 | 95.9% | Self-reported | |
| IFEval | text | 0.90 | 90.4% | Self-reported | |
| MATH | text | 0.89 | 89.0% | Self-reported | |
| HumanEval | text | 0.88 | 87.8% | Self-reported | |
| BIG-Bench Hard | text | 0.88 | 87.6% | Self-reported | |
| DocVQA | multimodal | 0.87 | 86.6% | Self-reported | |
| AI2D | multimodal | 0.84 | 84.5% | Self-reported | |
| Natural2Code | text | 0.84 | 84.5% | Self-reported | |
| ChartQA | multimodal | 0.78 | 78.0% | Self-reported | |
| Global-MMLU-Lite | text | 0.75 | 75.1% | Self-reported |
Showing 1 to 10 of 26 benchmarks