Gemini 1.5 Pro vs GPT-4o: Best for documents, images & content teams?
We fed both models 100-page legal contracts, 2-hour podcast transcripts, and mixed image+text tasks — then scored them blind on accuracy, cost, and speed. This is the full breakdown for content and document-heavy teams.
📊 Head-to-head specs
| Feature | Gemini 1.5 Pro | GPT-4o | Claude 3.5 Sonnet |
|---|---|---|---|
| Context window | 1,000,000 tokens 🏆 | 128,000 | 200,000 |
| Input price /1M tokens | $1.25 🏆 | $5.00 | $3.00 |
| Output price /1M tokens | $5.00 🏆 | $15.00 | $15.00 |
| Native image input | ✅ Yes | ✅ Yes | ✅ Yes |
| Native video input | ✅ Yes | ❌ No | ❌ No |
| Avg latency (first token) | 1.1s | 0.7s 🏆 | 0.8s |
| Rate limits (free tier) | 360 RPM | 500 RPM | 50 RPM |
📄 Long-document benchmark (100-page legal contract)
We used a 72,000-token legal contract (NDA + SaaS terms) and asked all models to: (1) identify clauses that deviate from standard terms, (2) flag liability exposure, (3) produce an executive summary. Scored by a paralegal (blind).
| Task | Gemini 1.5 Pro | GPT-4o | Claude 3.5 Sonnet |
|---|---|---|---|
| Clause identification accuracy | 94% | 88% | 96% 🏆 |
| Liability flag precision | 89% | 82% | 92% 🏆 |
| Summary quality (1–10) | 7.8 | 8.2 | 8.7 🏆 |
| Cost per document | $0.09 🏆 | $0.36 | $0.22 |
| Processing time | 28s | 14s 🏆 | 21s |
🖼️ Multimodal tasks (image + text)
We tested on a set of 50 product images (e-commerce), 20 charts (financial data), and 10 screenshots (UI bug reports). Models were asked to describe, extract data, and suggest actions.
| Task type | Gemini 1.5 Pro | GPT-4o |
|---|---|---|
| Product image description accuracy | 91% | 94% 🏆 |
| Chart data extraction (exact match) | 87% 🏆 | 83% |
| UI bug report from screenshot | 78% | 89% 🏆 |
| Cost per 50 images | $0.31 🏆 | $1.15 |
📹 Video analysis (Gemini exclusive)
Gemini 1.5 Pro is the only model in this comparison that accepts raw video input. We tested 5 webinar recordings (~30 min each) asking for summaries, speaker identification, and action items.
- Average summary accuracy: 88% (vs. human transcriptionist baseline)
- Cost per 30-min video: ~$0.45
- GPT-4o required manual transcription first ($0.006/min with Whisper) → ~$0.18 extra overhead
🏁 Our verdict
For document-heavy and long-context workloads, Gemini 1.5 Pro wins on price. Its 1M token context window lets you process entire codebases or books in one shot. For quality and multimodal tasks where cost is secondary, GPT-4o is the better performer.
- 🟢 Choose Gemini 1.5 Pro if: you process long documents at volume, need native video analysis, or are cost-constrained
- 🔵 Choose GPT-4o if: you need best-in-class multimodal quality, fast latency, or you're already in the Azure/Microsoft ecosystem
- 🟣 Consider Claude 3.5 Sonnet if: pure text quality is your priority and you need 200K context