Pricing Overview
Up to date prices are always available via endpoint /price-calculation for the selected model
| Task Type | Pricing Metric | Example Rate | Notes |
|---|---|---|---|
| Text-to-Image (Flux.1 schnell) | resolution × steps | 0.00136 USD for 512x512, 4 steps | Uses Flux Schnell as baseline in sample calculator |
| Text-to-Image (Z-Image-Turbo INT8) | resolution × steps | 0.00405 USD for 512x512, 4 steps | Generates very realistic images |
| Image-to-Image | steps (style transfer) | ~0.0132 USD for 512x512, 20 steps | Cost scales with steps and GPU time |
| Text-to-Speech (TTS) | number of characters | 0.77 USD per 1 M characters | Adjustable speed multipliers (fast = 0.5× cost, slow = 2× cost) |
| Text-to-Video | video duration + resolution | 0.001737 USD for 2s, 256×256 | 2–5 second clips; higher res or steps increase cost |
| Image-to-Video | source image + motion interpolation | 0.001737 USD for 2s, 256×256 | 2–5 second output, smooth motion |
| Video-to-Text (X, Twitch, Kick, YT Transcription) | video length | from 0.021 USD per hour | Supports timestamps, multilingual |
| Image-to-Text (OCR) | output characters | 0.00928 USD per 1,000 output chars (for 1024×1024 images) | Also includes object detection, scene understanding |
| Text-to-Embedding | number of tokens processed | 0.000068 USD per 1,000 tokens | Supports large-scale semantic search and RAG; cost scales linearly with token count |
Pricing by Task
Text-to-Image (Image Generation)- Users define width, height, steps via the API or UI.
- Public example: Flux Schnell model is used to estimate cost in the UI; for example, 512x512 at 4 steps gives 0.00136 USD. For the Z-Image-Turbo INT8 model with the same parameters, the price is 0.00405 USD, but the advantage is very realistic images.
- Higher resolutions and more steps yield better quality but incur higher cost.
- Important: For models other than Flux Schnell, pricing is model-specific and calculated on the server side.
- Charged per character in your input (e.g. 1M characters → 0.77 USD).
- Playback speed modifiers:
- Standard (1.0×): base cost
- Fast (2.0×): 0.5× the base cost
- Slow (0.5×): 2.0× the base cost
- Useful tip: using faster playback (2×) for drafts can reduce cost by ~50%.
- Price depends on clip duration (2–5 seconds) and resolution.
- Example public rate: 0.001737 USD for a 2-second clip at 256x256.
- You can scale resolution or duration, but cost increases accordingly.
- Transforms an existing image based on a new prompt or style.
- Pricing scales with the number of inference steps and GPU time required — similar to Text-to-Image tasks.
- Example: a 20-step transformation costs roughly the same as generating a 512×512 image.
- Fewer steps → faster & cheaper transfers; more steps → better fidelity.
- Transform a static image into a motion clip (2–5 seconds) with interpolation.
- Example: 256x256 for 2 seconds costs 0.001737 USD.
- Use lower resolution or shorter duration to reduce cost.
- Use motion parameters in prompts to guide movement.
- Billed per hour of video processed.
- Sample public rate: 0.021 USD per hour.
- For 5 minutes, cost is estimated at 0.003613 USD.
- Supports timestamps, multilingual transcription, and batching for better throughput.
- Charged based on number of characters recognized in output.
- Baseline rate: 0.00928 USD per 1,000 output characters (for 1024×1024 images).
- Example outputs:
- Single photo (≈20 chars) → 0.000186 USD
- Math expression (~350 chars) → 0.0032 USD
- Book page (~1,500 chars) → 0.0139 USD
- Volume discounts available for bulk processing (100k+ images)—contact sales.
- Pricing is based on the number of tokens processed.
- Sample public rate: 0.000093 USD per 1,000 tokens (client-side pricing).
- Embeddings are typically used for semantic search, retrieval-augmented generation (RAG), clustering, and similarity matching.
- Costs scale linearly with token count, making it efficient even at large volumes.
- Important: Different embedding models may have varying dimensionality (e.g. 768 vs. 1024), but pricing is standardized per token for simplicity.
Best Practices & Guidance
- Use the public calculator as a guide, but always rely on the API’s final cost calculation (model + parameters).
- Avoid hardcoding prices or cost assumptions—always fetch or compute cost based on actual model usage.
- For reproducibility (e.g. in production or experiments), pin model versions and seeds so results are consistent across runs.
- Prepare fallback options in your integration: if a model is deprecated or disabled, switch to a sensible alternative automatically.
- Monitor usage and budget: higher resolution, longer clips, or more steps increase costs proportionally.
Link to live pricing page for reference: https://deapi.ai/#pricing