There is no evidence-based single winner for prompt following or filter strictness. The practical differences are in how each service accepts instructions, lets you revise a result, handles a blocked request, and exposes safety controls. Gemini’s consumer app is conversational but its API exposes adjustable safety thresholds; OpenAI documents refusal before generation and blocking after generation; Midjourney offers explicit parameters, Remix and regional regeneration; and Adobe Firefly emphasizes licensed training data and Content Credentials. Choose the workflow and privacy model that fit your project rather than relying on an unsupported “best” ranking.
What this comparison can—and cannot—tell you
Prompt adherence and moderation are often discussed as if they were one score. They are not. A generator may follow a long visual description well but offer little control over a blocked request. Another may provide excellent region editing while keeping its safety decisions mostly opaque. The same company can expose different behavior in a consumer app and an API.
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The official documents reviewed for Gemini, ChatGPT Images, GPT-4o image generation, Midjourney and Firefly do not provide a controlled, current, cross-platform test of prompt accuracy, image quality, false refusals or refusal rates. They describe product features, policy rules and safety architecture. That is not enough to call one service the “best follower” or the “strictest filter.” A fair ranking would require the same prompts, model versions, account or API surfaces, repeated runs and published results for both generations and refusals.
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| Service or surface | Prompt controls | Editing and iteration | Safety behavior documented by the vendor | Privacy or provenance notes |
|---|---|---|---|---|
| Google Gemini app | Natural-language instructions; Google recommends an action, style, subject, action and setting. | Conversational refinement in the app; consumer filter-tuning controls are not documented here. | Images may be removed when systems detect a possible violation of Google’s Terms or Prohibited Use Policy. | Consumer-app visibility and training treatment are not established by the cited help page. |
| Gemini API | Request-based generation through the API, with model-specific settings. | Application developers control their own iteration flow. | Harassment, hate speech, sexually explicit content and dangerous-content categories; thresholds from BLOCK_NONE through BLOCK_LOW_AND_ABOVE for documented settings, plus prompt feedback and candidate safety ratings. |
API behavior and defaults are separate from the consumer app. |
| ChatGPT Images 2.0 | Chat-style natural-language prompting. | Conversation-based refinement; the cited safety page focuses on the safety stack rather than a complete editing specification. | Upstream classifiers assess a request before it reaches the image model and can refuse it. | Do not infer a comparative strictness ranking from the architecture description. |
| GPT-4o native image generation | Natural-language prompting through the chat model. | Chat model can decide whether to trigger generation; output handling includes a separate blocking layer. | The addendum describes chat refusal before generation and post-generation blocking, including CSAM classifiers and a safety-focused reasoning monitor. | OpenAI reports red-team and automated evaluations, but not cross-vendor scores. |
| Midjourney | Natural-language prompts plus explicit parameters such as --ar for width-to-height ratio. |
Remix changes prompt text during variations; Vary Region regenerates a selected area. | Creations remain subject to moderation and community rules; Stealth does not exempt images. | Website creations are public by default. Stealth is included with Pro or Mega plans; public Discord posts can still be visible. |
| Adobe Firefly | Prompt-driven generation inside Firefly and Adobe workflows; feature availability depends on the plan. | Firefly tools and partner-model options vary by feature and entitlement. | Adobe describes its Firefly models as producing commercially safe results; partner-model policies must be checked separately. | Adobe says current Firefly models use licensed content, including Adobe Stock, and public-domain content. Certain exports can include Content Credentials. |
Google Gemini: simple consumer prompts, adjustable API thresholds
How the Gemini app expects a prompt
Google’s Gemini Apps Help recommends beginning with an action such as “draw,” “generate,” or “create,” then specifying the visual style, subject, action and setting. This ordering gives the model an explicit job before adding details such as lighting, composition or materials. For example, a request can identify the action first, name a documentary-photography style, describe the subject and then locate it in a particular setting.
#1 Best Overall
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The consumer help page also says an image may be removed if Google’s systems detect a possible violation of its Terms or Prohibited Use Policy. It explains why an apparently successful generation can disappear, but it does not document a user-facing control for lowering or raising the filter threshold. Do not treat the absence of a visible control as proof that the app has no moderation layers; it means the cited consumer documentation does not expose a tuning interface.
What developers can tune in the Gemini API
The Gemini API is a different product surface. Its safety-settings documentation lists harassment, hate speech, sexually explicit content and dangerous content categories. For the settings documented there, a developer can choose thresholds from BLOCK_NONE through BLOCK_LOW_AND_ABOVE on a request-by-request basis. When content is blocked, the API can return prompt feedback or candidate safety ratings so an application can explain the outcome or route it for review.
Google’s documentation states that when no threshold is set, the default is Off for Gemini 2.5 and Gemini 3 models. That statement is model- and API-specific, not a description of the Gemini consumer app, and it should be rechecked whenever the model or API version changes. A lower threshold setting does not authorize content that violates Google policy; developers remain responsible for complying with the applicable rules.
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Google’s current Gemini API image documentation says, “Imagen models are shut down.” It describes Imagen as a legacy image-generation model no longer available in that API and directs developers toward Nano Banana models, including gemini-2.5-flash-image and Nano Banana 2 model names such as gemini-3.1-flash-image, using generate_content or generateContent. The consumer Gemini app can have different model availability, so an app experience should not be used to infer API availability.
Rank #2
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OpenAI image generation: safety decisions before and after rendering
ChatGPT Images 2.0 upstream refusal
OpenAI’s ChatGPT Images 2.0 safety-stack description places classifiers before the image-generation model. They assess the request upstream, and a request judged to violate policy is refused before it is sent to the image model. This can feel different from a generation that completes and is then removed: the user receives a refusal at the request stage rather than an image followed by a warning.
GPT-4o’s two documented layers
OpenAI’s GPT-4o native image-generation addendum describes the chat model as a first line of defense. It may refuse to trigger image generation, while a separate post-generation layer can block an output. The controls described include CSAM classifiers and a safety-focused reasoning monitor. This addendum and the ChatGPT Images 2.0 page describe related but separate documents; they should not be silently combined into one version-specific specification.
The addendum says OpenAI used vetted external red teamers and automated evaluations to measure both unsafe outputs and incorrect refusals of compliant requests. It does not publish a result that can be compared numerically with Gemini, Midjourney or Firefly. A refusal therefore tells you about that request, model and policy path—not where the service sits on a universal strictness scale.
Midjourney: the most explicit prompt-and-region controls in this set
Parameters for composition
Midjourney documents --ar as a width-to-height ratio parameter. Adding it to a prompt gives the model an explicit canvas shape instead of relying on an interface default. This is useful when a design must fit a portrait poster, a landscape banner or another fixed placement.
Remix for changing the instruction
Remix mode lets you edit prompt text while creating variations. Rather than starting over, you can retain the composition and alter a subject attribute, style direction or scene detail. Because each variation remains stochastic, a changed prompt is an instruction to explore a new result, not a guarantee that every unchanged element will remain identical.
Rank #3
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Vary Region for local fixes
Vary Region lets you select part of an image and regenerate that area. It is the clearest documented answer in this comparison to “Can I edit only one part?” Selective regeneration can repair a hand, replace a sign or alter a background while preserving the rest of the composition, although the boundary and surrounding context still influence the replacement.
Public-by-default visibility
Midjourney’s FAQ says creations on its website are public by default. Stealth is included with Pro or Mega plans, but private creations still follow Midjourney’s Terms and Community Guidelines, and the team can view Stealth images for moderation. Images made in public Discord channels can remain visible there, so website Stealth is not universal privacy.
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What Adobe says about training data
Adobe says current Firefly generative-AI models are trained on licensed content, including Adobe Stock, and public-domain content. It also describes Content Credentials as tamper-evident information that can record details such as an asset’s creation date, tools and edits; certain Firefly exports automatically include them.
These are Adobe’s descriptions of its own models and workflows. They are not a guarantee that every image created inside an Adobe application used a Firefly model. If a workflow offers a partner model, investigate that model’s training, licensing and provenance terms separately.
Rank #4
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Credits and commercial-use limits
Adobe’s generative-credit documentation describes monthly allocations and plan-specific access to standard or premium features. Some Firefly and partner-model generations consume credits. Credit use and commercial-use terms depend on the plan, feature, beta status and model, so there is no single credit allowance or universal price to apply across Firefly.
Adobe’s comparison teaching page characterizes Firefly models as producing commercially safe results. That is Adobe’s product characterization, not an independent legal conclusion. Keep records of the model and plan used when an image will enter a commercial workflow.
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How to choose by workflow instead of by a supposed ranking
Choose Gemini when you want conversational direction or API feedback
The Gemini app suits people who prefer to describe an image in ordinary language and refine it through dialogue. Developers who need category-specific thresholds and machine-readable feedback should evaluate the Gemini API separately, including its current model names and default behavior.
Choose OpenAI when refusal-stage behavior matters
OpenAI’s published descriptions are useful when you need to understand whether a request can be rejected before generation and whether a completed output can be blocked afterward. Treat the documented layers as an architecture explanation, not as proof that the service blocks more or less than another tool.
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- Tilt Function Battery-free Stylus: This computer graphics tablet come with a battery-free stylus PW100, no need to charge, allowing for constant uninterrupted drawing. ±60° tilt support enables imitation of lines input with diverse drawing gestures, with accuracy ensured.
- Press Keys:12 programmable press keys plus 16 programmable soft keys, you can set shortcut keys on drawing tablet's driver based on your preferences, such as erase, zoom in/out, scroll up and down, and so on.
- Compatibility: HUION graphics tablet supports Windows 7 or later/ macOS 10.12 or later/ Android 6.0 or later/ Linux (Ubuntu). A USB adapter is required to connect to a Mac computer. H1060P supports various mainstream design and drawing software, including PS, SAI, AI, CDR, etc. (Please note: The H1060P is compatible with Ubuntu, but it requires the use of the Xorg display server. Wayland is not supported.)
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Choose Midjourney when composition and local variation are central
The combination of --ar, Remix and Vary Region makes Midjourney attractive for iterative visual direction. Budget for the public-by-default website model or a plan with Stealth, and remember that public Discord activity can expose work regardless of website settings.
Choose Firefly when provenance documentation is a priority
Firefly is the clearest fit when your team values Adobe’s stated licensed-training approach and Content Credentials in supported exports. Verify the exact model, plan, credit consumption and commercial terms for every feature, especially when a partner model is involved.
A practical prompt-and-editing workflow
- Define the deliverable. State whether the output is a portrait, banner, product concept, editorial illustration or another format, and include the required aspect ratio when the service supports it.
- Give the model an action. For Gemini, begin with “draw,” “generate” or “create,” then name the subject, action and setting.
- Add visual constraints. Specify viewpoint, lighting, palette, medium, era, level of realism, text requirements and what must remain out of frame.
- Generate a small set of candidates. Keep the prompt stable while comparing candidates so you can tell whether a change came from the instruction or normal sampling variation.
- Change one variable at a time. Use conversational refinement, Remix or an equivalent revision path rather than rewriting every detail after each attempt.
- Use local editing where available. Select only the region that needs correction, as with Midjourney’s Vary Region, and describe the replacement together with the surrounding context.
- Record the run. Save the service, model, date, prompt, parameters, plan or API surface and any refusal message. This is essential for reproducibility because model names and policies change.
Why a prompt can be blocked—and what to do next
A block can occur before generation, during a chat model’s decision to invoke an image model, or after an image has been rendered. It can reflect a policy category, a classifier threshold, a safety monitor or a post-generation review. A disappearance from the interface is not necessarily a technical failure.
- Read the exact feedback. Gemini API responses may include prompt feedback or candidate safety ratings; consumer apps may provide less detail.
- Remove ambiguous wording and describe a legitimate, non-sensitive purpose directly. Do not attempt to disguise prohibited content.
- Separate benign components of a complex request and test which component triggers the refusal.
- Check the correct product surface. A consumer app and an API can have different controls, defaults and model availability.
- Do not try to circumvent safety filters. Google’s policy expressly prohibits manipulating a model to contravene policy or bypass abuse protections.
- If the request is clearly compliant but repeatedly refused, document the prompt, model and response and use the provider’s support or feedback channel.
How to run a fair prompt-following and safety test
If you need an internal answer to “which follows prompts best?” create a dated evaluation rather than relying on anecdotes. Use identical wording where the interfaces permit it, and record any required syntax such as Midjourney parameters or API request fields.
- Declare the exact service, model name, app or API surface, account tier and test date.
- Build prompt groups covering composition, text in images, multiple subjects, spatial relationships, style constraints and benign edge cases.
- Repeat each prompt several times to account for random variation.
- Score each output against pre-written criteria, not personal enthusiasm for one image.
- Log successful generations, pre-generation refusals, post-generation blocks, errors and apparent false refusals separately.
- Publish the full protocol and examples if you make a public claim. A small private trial can guide a purchase decision, but it is not a universal benchmark.
Details that change quickly
Model names, API availability, safety defaults, consumer controls, subscription entitlements, privacy plans and credit rules are volatile. Google’s statement that Imagen models are shut down, the Gemini 2.5 and 3 API default described as Off when no threshold is set, Midjourney plan access to Stealth, and Adobe’s credit entitlements should all be verified against the current documentation before a production decision. The architecture and policy descriptions above explain how the vendors say their systems work; they do not replace a hands-on test of your own prompts.
The Bottom Line
Compare control surfaces, not imagined league tables: Gemini separates conversational use from API thresholds, OpenAI documents refusal and post-generation layers, Midjourney exposes parameter and region-editing tools, and Firefly emphasizes Adobe’s provenance workflow. Run a dated, same-prompt test for your own subject matter, and verify privacy, credits, model availability and policy terms at the moment you deploy.
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