Image Token Calculator
Adjust image dimensions to calculate token usage across GPT-4o, Claude, and Gemini in real-time. Optimize resolution to save on multimodal API costs.
LLM (GPT-5.5, Claude, DeepSeek) calling costs are 30% - 50% lower than official APIs. Multimodal (Veo 3.1, Flux Pro) costs are 60%+ lower!
Single key aggregates text, image, video generation (Runway, Veo, Kling), music generation (Suno), and speech recognition. No multiple accounts needed.
Fully compatible with OpenAI / Anthropic request formats. Simply update base_url and api_key in your code to migrate seamlessly.
Developer Integration Guides (Cursor, Claude Code, SDK)
Image Tokens FAQ
Q: How does OpenAI calculate image tokens?
OpenAI offers Low and High detail modes. Low detail costs a flat 85 tokens per image. High detail scales the image to fit a 2048x2048 grid (with shortest side at most 768px), then splits it into 512x512px tiles. Each tile costs 170 tokens, plus an 85-token base cost.
Q: Why is high-resolution image input so expensive?
Because vision models split images into attention tiles. A single 4K image can be sliced into a dozen 512x512 tiles, consuming over 2,000 tokens (equivalent to thousands of words). Downscaling images before sending them to the API can cut your multimodal bill by up to 80%.
Mainstream Model Division Rules
Different AI providers implement distinct mathematical formulas to compress images into inputs:
- OpenAI (o1 / o3 / GPT-4o): Based on 512x512 tiles. For example, a 1024x1024px image is cut into 2x2 = 4 tiles, resulting in `4 * 170 + 85 = 765` tokens.
- Anthropic (Claude 3.5 / 3.7): Calculates linearly with `Tokens = (Width * Height) / 750`. A 1024x1024px image roughly costs around 1400 tokens.
- Google (Gemini 2.5 / 3.5): If any dimension exceeds 384px, Gemini splits the image into 768x768 tiles. Each tile costs a flat 258 tokens.