Side-by-side comparison to help you choose the right tool for your business
Our Verdict: Stable Diffusion wins by default — DALL-E was retired May 12, 2026 (successor: gpt-image-2)
Important update: OpenAI shut down DALL-E 2 and DALL-E 3 on May 12, 2026, so DALL-E can no longer be adopted — Stable Diffusion (current flagship: Stable Diffusion 3.5) wins this matchup by default. OpenAI's current image model is gpt-image-2, priced per token ($8/1M input + $30/1M output) rather than per image. If you want a managed OpenAI API, evaluate gpt-image-2; if you want free, infinitely customizable generation at scale, Stable Diffusion remains the engineering team's pick. The comparison below is preserved for historical context.
No longer available — new integrations should use gpt-image-2
Discontinued May 12, 2026 — successor gpt-image-2: $8/1M input + $30/1M output tokens (API)
beginner
N/A (retired)
Technical teams needing unlimited, customizable image generation at scale
Free (open-source) / Cloud APIs: $0.002-0.05 per image
advanced
1-2 weeks
| Feature | DALL-E | Stable Diffusion |
|---|---|---|
| Availability | Retired May 2026 (successor: gpt-image-2) | Active (Stable Diffusion 3.5) |
| Ease of use | Was excellent (in ChatGPT) | Requires setup |
| Text in images | Was best-in-class | Poor |
| Self-hosting | No | Yes |
| Fine-tuning | No | Full (LoRA, DreamBooth) |
| API access | Via successor gpt-image-2 | Open / self-hosted |
| Cost at scale | Successor: $8/1M in + $30/1M out tokens | Free (self-hosted) |
DALL-E is retired; of the two tools compared here, only Stable Diffusion is still available (ChatGPT users get OpenAI's newer gpt-image models instead)
Self-hosted means generating thousands of images with zero marginal cost
DALL-E's API role passed to gpt-image-2, OpenAI's current image model
Open-source license and self-hosting give you full control in your product
We implement both options. Tell us your use case and we'll recommend the right fit — then set it up for you.
No. OpenAI shut down dall-e-2 and dall-e-3 on May 12, 2026. OpenAI's current image model is gpt-image-2, billed per token ($8 per 1M input + $30 per 1M output) rather than per image. Existing DALL-E integrations need to migrate to gpt-image-2 or an alternative like Stable Diffusion.
DALL-E 3 had a significant edge in prompt accuracy before its retirement. Stable Diffusion requires more prompt engineering skill, but experienced users can achieve highly specific results with negative prompts, ControlNet, and IP-Adapter. For OpenAI's current prompt-following, evaluate gpt-image-2.
Yes, via cloud APIs from services like Replicate, Stability AI, or Hugging Face Inference. You'll pay per image but avoid hardware costs. For occasional use, this is the practical path. For heavy use, a local GPU pays for itself quickly.
Stable Diffusion with a custom LoRA fine-tuned on your brand assets gives you the most consistent results. Prompt-only consistency (the DALL-E approach, now carried by gpt-image-2) is inherently less reliable. If brand precision matters, invest in the Stable Diffusion fine-tuning.
Images previously generated with DALL-E on paid plans keep the commercial rights granted under OpenAI's terms at the time. Stable Diffusion's open license is permissive, but check the specific model license — some community fine-tunes have different restrictions. For client work, we always verify the license chain.
More head-to-head matchups for the tools in this comparison
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