Phi-3.5-mini-instruct
Zero-eval
#1Qasper
#1SQuALITY
#1QMSum
+11 more
by Microsoft
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About
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
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Pricing Range
Input (per 1M)$0.10 -$0.10
Output (per 1M)$0.10 -$0.10
Providers1
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Timeline
AnnouncedAug 23, 2024
ReleasedAug 23, 2024
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Specifications
Training Tokens3.4T
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License & Family
License
MIT
Performance Overview
Performance metrics and category breakdown
Overall Performance
31 benchmarks
Average Score
58.7%
Best Score
86.2%
High Performers (80%+)
4Performance Metrics
Max Context Window
256.0KAvg Throughput
23.0 tok/sAvg Latency
1ms+
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All Benchmark Results for Phi-3.5-mini-instruct
Complete list of benchmark scores with detailed information
| GSM8k | text | 0.86 | 86.2% | Self-reported | |
| ARC-C | text | 0.85 | 84.6% | Self-reported | |
| RULER | text | 0.84 | 84.1% | Self-reported | |
| PIQA | text | 0.81 | 81.0% | Self-reported | |
| OpenBookQA | text | 0.79 | 79.2% | Self-reported | |
| BoolQ | text | 0.78 | 78.0% | Self-reported | |
| RepoQA | text | 0.77 | 77.0% | Self-reported | |
| Social IQa | text | 0.75 | 74.7% | Self-reported | |
| MEGA XStoryCloze | text | 0.73 | 73.5% | Self-reported | |
| MBPP | text | 0.70 | 69.6% | Self-reported |
Showing 1 to 10 of 31 benchmarks
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