# Claude Opus 4.5 vs. Gemini 3 Pro: Knowledge Base Q&A Comparison

**Analysis Date:** December 2025
**Use Case:** Cost-efficient Q&A chat informed by rich PDF document knowledge bases

---

## Executive Summary

This analysis compares Claude Opus 4.5 and Gemini 3 Pro for building knowledge base Q&A systems that leverage rich PDF documents (including charts, tables, and images—not just extracted text). Key findings:

- **Gemini 3 Pro** offers a 5× larger context window (1M vs 200K tokens) and automatic implicit caching
- **Claude Opus 4.5** excels at reasoning quality and Office file creation
- Both offer ~90% cost savings on cached content reads
- Neither natively supports EPUB files (preprocessing required)

---

## Context Window Size

| Model | Context Window | Notes |
| ------- | --------------- | ------- |
| **Gemini 3 Pro** | 1M tokens | Can comprehend text, audio, images, video, PDFs, and entire code repositories |
| **Claude Opus 4.5** | 200K tokens | Claude Sonnet 4.5 supports 1M tokens with beta header, but Opus 4.5 remains at 200K |

**Winner: Gemini 3 Pro** — its 1M token window is 5× larger than Opus 4.5's standard 200K, allowing you to fit significantly more documents in a single context.

---

## Context Caching & Cost Efficiency

### Gemini 3 Pro Caching

- **90% discount** on cached token reads (Gemini 2.5+ models)
- **Minimum cache size:** 2,048 tokens
- **Implicit caching:** Enabled by default—automatic cost savings without manual configuration
- **Multimodal caching:** Cached content can include text, PDF, image, audio, or video
- **Cache TTL:** Default 1 hour, customizable

### Claude Opus 4.5 Caching

- **90% discount** on cache reads (0.1× base input price)
- **Cache write cost:** 1.25× base input price (5-minute TTL) or 2× (1-hour TTL)
- **Cache TTL:** 5 minutes default, 1 hour optional
- **Manual configuration:** Requires explicit `cache_control` parameters
- **Cache breakpoints:** Up to 4 per prompt

### Pricing Comparison (per million tokens)

| Model | Base Input | Base Output | Cache Read | Cache Write |
| ------- | ----------- | ------------- | ------------ | ------------- |
| Gemini 3 Pro (≤200K context) | $2.00 | $12.00 | ~$0.20 | Standard |
| Gemini 3 Pro (>200K context) | $4.00 | $18.00 | ~$0.40 | Standard |
| Claude Opus 4.5 | $5.00 | $25.00 | $0.50 | $6.25 (5m) / $10.00 (1h) |
| Claude Sonnet 4.5 | $3.00 | $15.00 | $0.30 | $3.75 (5m) |

### Cost Savings Example

For a knowledge base with 500K tokens queried 100 times:

| Scenario | Gemini 3 Pro | Claude Opus 4.5 |
| ---------- | -------------- | ----------------- |
| First query (cache write) | $2.00 | $6.25 |
| 99 subsequent queries (cache read) | $19.80 | $49.50 |
| **Total** | **$21.80** | **$55.75** |

**Winner: Gemini 3 Pro** — lower base rates plus automatic implicit caching means less manual configuration and lower costs, especially for large corpora.

---

## Native PDF Support

### Claude PDF Capabilities

- Works with any standard PDF
- Can analyze text, pictures, charts, and tables
- Uses vision capabilities (each page converted to image)
- Token cost: 1,500-3,000 tokens per page depending on content density
- **Limits:** 32 MB or 100 pages per API request
- Available on all active Claude models

### Gemini 3 Pro PDF Capabilities

- Native PDF processing without image conversion
- Can comprehend PDFs alongside text, audio, images, and video
- PDFs can be cached at full resolution within the 1M token context
- Supports caching from 2,048 tokens up to the full context window

### Comparison

| Feature | Claude | Gemini 3 Pro |
| --------- | -------- | -------------- |
| Max PDF size | 32 MB / 100 pages | Limited by context window |
| Processing method | Page → Image → Vision | Native multimodal |
| Chart/table understanding | ✅ Yes | ✅ Yes |
| Caching PDFs | ✅ Yes | ✅ Yes (implicit) |
| Visual fidelity | High | High |

**Winner: Gemini 3 Pro** — the 1M context window allows loading entire document corpora with native PDF understanding and automatic caching.

---

## Office Format Support (PPTX, DOCX, XLSX)

### Claude Capabilities

**Reading/Analysis:**

- Can process uploaded DOCX, XLSX, PPTX files
- Extracts and analyzes content including tables, charts, formatting

**Creation/Editing:**

- First to ship unified four-format file creation: `.xlsx`, `.pptx`, `.docx`, `.pdf`
- Can create Excel spreadsheets with working formulas
- Can generate PowerPoint presentations with layouts and visuals
- Can produce Word documents with formatting
- Direct Google Drive integration for saving

### Gemini Capabilities

**Reading/Analysis (Web/Mobile App):**

- DOC, DOCX, PDF, RTF, DOT, DOTX, HWP, HWPX, TXT, Google Docs
- PPTX and Google Slides (slide-by-slide summarization)
- XLS, XLSX, CSV, TSV, Google Sheets

**Reading/Analysis (API):**

- DOCX files can be uploaded but **cannot be used for generating content** via API
- Workaround: Convert to PDF first
- Native Google Workspace integration

**Creation:**

- Can work with Google native docs (Docs, Sheets, Slides)
- Cannot create standalone Excel, PowerPoint, or Word files

### Comparison Matrix

| Capability | Claude | Gemini 3 Pro |
| ------------ | -------- | -------------- |
| **Read DOCX** | ✅ Full | ⚠️ App only, API limited |
| **Read XLSX** | ✅ Full | ✅ Full |
| **Read PPTX** | ✅ Full | ✅ Full |
| **Create DOCX** | ✅ Yes | ❌ No |
| **Create XLSX** | ✅ Yes | ❌ No (Sheets only) |
| **Create PPTX** | ✅ Yes | ❌ No (Slides only) |
| **Edit existing files** | ✅ Yes | ⚠️ Google formats only |

**Winner: Claude** — significantly stronger Office format creation and editing capabilities. Gemini has broader reading support in the consumer app but API limitations for DOCX.

---

## EPUB Support

**Neither Claude nor Gemini natively supports EPUB files.**

EPUB files are essentially ZIP archives containing XHTML/HTML content. LLMs process text—file format parsing happens at the application layer.

### Workarounds

1. **Extract content programmatically:**

   ```python
   import ebooklib
   from ebooklib import epub

   book = epub.read_epub('book.epub')
   for item in book.get_items_of_type(ebooklib.ITEM_DOCUMENT):
       content = item.get_content()
       # Process HTML content
   ```

2. **Convert EPUB → PDF:**
   - Use Calibre or similar tools
   - Then process PDF natively with either model

3. **Convert EPUB → Markdown/Text:**
   - Tools like `pandoc`: `pandoc book.epub -o book.md`
   - Send text content directly to API

### Recommendation for EPUB Knowledge Bases

Build a preprocessing pipeline:

1. Extract EPUB content to clean text/HTML
2. Optionally convert to PDF for visual fidelity
3. Cache the processed content using your chosen model's caching mechanism

---

## Additional Considerations

### Batch Processing Discounts

| Model | Batch Discount | Use Case |
| ------- | --------------- | ---------- |
| Claude | 50% off all models | Non-urgent, async processing |
| Gemini | 50% off all paid models | Bulk data processing |

### Rate Limits & Throughput

| Model | Throughput |
| ------- | ----------- |
| Gemini 3 Pro | Up to 1M tokens per minute |
| Claude Opus 4.5 | Varies by usage tier |

### Model Strengths Beyond Pricing

| Strength | Claude Opus 4.5 | Gemini 3 Pro |
| ---------- | ----------------- | -------------- |
| Deep reasoning | ✅ Excellent | ✅ Excellent (Deep Think mode) |
| Code generation | ✅ Best-in-class | ✅ Strong |
| Prompt injection resistance | ✅ Industry-leading | ✅ Good |
| Multimodal (native) | ⚠️ Vision-based | ✅ Native multimodal |
| Tool use | ✅ Advanced | ✅ Advanced |
| Extended thinking | ✅ Effort parameter | ✅ Thinking levels |

---

## Recommendation Summary

### Choose Gemini 3 Pro if

- ✅ Your primary need is **large-scale PDF knowledge base Q&A**
- ✅ You need to fit **more documents in context** (1M tokens)
- ✅ You want **automatic caching** without manual configuration
- ✅ **Cost efficiency** is a primary concern
- ✅ You're already in the **Google Cloud ecosystem**

### Choose Claude Opus 4.5 if

- ✅ You need **superior reasoning** for complex analysis
- ✅ You need to **create Office documents** (XLSX, DOCX, PPTX)
- ✅ **Prompt injection resistance** is critical
- ✅ You need **fine-grained control** over caching behavior
- ✅ Your documents fit within **200K tokens**

### Hybrid Approach

Consider using both:

- **Gemini 3 Pro** for ingestion, caching, and initial Q&A on large corpora
- **Claude Opus 4.5** for high-value reasoning tasks, document generation, and complex analysis

---

## Quick Reference: Feature Comparison Matrix

| Feature | Claude Opus 4.5 | Gemini 3 Pro | Winner |
| --------- | ----------------- | -------------- | -------- |
| Context window | 200K | 1M | Gemini |
| Base input price | $5/M | $2/M | Gemini |
| Cache read discount | 90% | 90% | Tie |
| Implicit caching | ❌ | ✅ | Gemini |
| Native PDF support | ✅ | ✅ | Tie |
| Max PDF per request | 100 pages | Context-limited | Gemini |
| DOCX reading (API) | ✅ | ⚠️ Limited | Claude |
| Office file creation | ✅ | ❌ | Claude |
| EPUB support | ❌ | ❌ | Tie |
| Reasoning quality | Excellent | Excellent | Tie |
| Batch discount | 50% | 50% | Tie |

---

## Appendix: API Code Examples

### Claude Prompt Caching (Python)

```python
import anthropic

client = anthropic.Anthropic()

response = client.messages.create(
    model="claude-opus-4-5-20251101",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "You are an expert analyst."
        },
        {
            "type": "text",
            "text": "<your_large_knowledge_base_content>",
            "cache_control": {"type": "ephemeral"}
        }
    ],
    messages=[
        {"role": "user", "content": "What are the key findings?"}
    ]
)
```

### Gemini Context Caching (Python)

```python
from google import genai

client = genai.Client()

# Create cache (automatic for implicit caching)
cache = client.caches.create(
    model="gemini-3-pro",
    contents=[
        {"role": "user", "parts": [{"text": "<your_large_knowledge_base_content>"}]}
    ],
    ttl="3600s"  # 1 hour
)

# Use cached content
response = client.models.generate_content(
    model="gemini-3-pro",
    cached_content=cache.name,
    contents=[{"role": "user", "parts": [{"text": "What are the key findings?"}]}]
)
```

---

*Analysis prepared December 2025. Pricing and capabilities subject to change. Always verify current pricing at [anthropic.com/pricing](https://anthropic.com/pricing) and [ai.google.dev/pricing](https://ai.google.dev/pricing).*
