FLUX.1 vs DALL·E 3

Side-by-side — pricing, strengths, tradeoffs, and fit.

FLUX.1

Open-weight text-to-image model from Black Forest Labs with state-of-the-art quality and API access.

DALL·E 3

OpenAI’s text-to-image model with strong prompt adherence and native ChatGPT + API access.

At a glance

Open SourceFree TierEnterprise
◌ Declining·From $0.003/image (API)
Free TierEnterprise
◐ Growing·From $0.04/image (API)

Overview

One-liner

Open-weight text-to-image model from Black Forest Labs with state-of-the-art quality and API access.

One-liner

OpenAI’s text-to-image model with strong prompt adherence and native ChatGPT + API access.

Maturity

Declining

Maturity

Growing

Open source

✓ Yes

Open source

✕ No

Pricing

Free tier

✓ Available

Open weights (schnell) are free to self-host

Free tier

✓ Available

Limited image generations in the free ChatGPT tier

Starts at

$0.003/image (API)

Starts at

$0.04/image (API)

Model

Usage-based

Model

Usage-based

Enterprise

✓ Available

Enterprise

✓ Available

Best for

✓ Best for

Developers wanting open weights and self-hostingRun locally with full control and no per-image fees (schnell)
API image generation with cost controlHosted via Replicate/fal at competitive per-image pricing

✓ Best for

Developers adding image generation to an app via APIDrop-in OpenAI API with strong prompt adherence
Use cases needing faithful, instruction-following outputBest-in-class adherence to detailed prompts

Not ideal for

✕ Not for

Non-technical users wanting a polished appNo consumer app — access is via API or self-hosted UIs
Commercial use of the dev weights without a licenseFLUX.1 [dev] is non-commercial; use schnell or Pro/API

✕ Not for

Maximum artistic stylizationMidjourney and Ideogram produce more striking creative output
Self-hosted or offline generationCloud-only API; no local deployment

Strengths

↑ Strengths

State-of-the-art quality for an open model
Self-hostable open weights
Broad ecosystem and API availability

↑ Strengths

Excellent prompt adherence
Trivial API integration on the OpenAI platform
Strong text rendering inside images

Weaknesses

↓ Weaknesses

Lack of official fine-tuning code and uncertainty regarding fine-tunability
Missing support for Apple Core ML
Poor error handling and lack of progress indicators for CPU-only or non-CUDA environments
Ineffective environment variable handling for local model caching

↓ Weaknesses

Less artistic polish than Midjourney
Limited fine-grained editing controls
Usage-based costs add up at scale
Full FLUX.1 profile →Full DALL·E 3 profile →