Gemini 1.5 Pro
Model Overview
Gemini 1.5 Pro is Google DeepMind’s flagship multimodal model, released on February 15, 2024. Its standout feature is the industry-leading 2 million token context window, enabling whole-codebase reasoning, multi-hour video understanding, and million-word document analysis in a single call. The model accepts text, image, audio, and video inputs natively, making it the only flagship that processes video as a first-class modality. Built on a mixture-of-experts architecture, Gemini 1.5 Pro delivers strong reasoning performance at roughly half the price of GPT-4o. It powers the Gemini Advanced consumer product, Google Cloud Vertex AI, and Google Workspace AI features. The long-context capability is particularly valuable for enterprises dealing with large legal contracts, financial filings, or research corpora.
Key Specifications
| Attribute |
Value |
| Vendor |
Google DeepMind |
| Version |
1.5-pro |
| Release Date |
2024-02-15 |
| Context Window |
2,000,000 tokens |
| Input Modalities |
text, image, audio, video |
| Output Modalities |
text |
| License |
Proprietary |
| Documentation |
https://ai.google.dev/gemini-api/docs |
| Benchmark |
Score |
Unit |
Notes |
| MMLU |
85.9 |
% |
5-shot |
| HumanEval |
71.9 |
pass@1 |
— |
| GSM8K |
91.7 |
% |
0-shot CoT |
| MATH |
58.5 |
% |
0-shot CoT |
| BBH |
84.0 |
% |
3-shot CoT |
Pricing
| Tier |
Price (per 1M tokens) |
| Input |
$1.25 |
| Output |
$5.00 |
| Cache Read |
$0.3125 |
| Cache Write |
$1.25 |
Pricing source: https://ai.google.dev/pricing (as of 2024-08-01).
Strengths
- Industry-leading 2M token context window for ultra-long inputs.
- Native video modality support, unique among flagship models.
- Competitive pricing — roughly half of GPT-4o.
- Strong multimodal grounding across text, image, audio, and video.
Weaknesses
- HumanEval score (71.9) trails GPT-4o and Claude 3.5 Sonnet on pure coding.
- Long-context recall can be inconsistent for facts buried deep in the input.
- Proprietary model with no self-host option.
Use Cases
- Whole-codebase refactoring and analysis.
- Long-video summarization and content moderation.
- Multi-document legal and financial research.
- Cross-modal retrieval over mixed media archives.
References