fal.ai
Calls itself a generative media platform for developers — queue-first image, video and audio APIs with a large first-party catalogue.
See the comparisonPlatform comparison
Compare us against the platform you are already using.
Find the differences that affect your NSFW workflow: available models, request mapping, total cost and spend controls. Each comparison also explains when the other platform is a better fit.
Method
How these pages are built
Start with one workflow you already use. Match its model version, task, inputs and output settings before comparing platform costs or moving traffic.
- Every claim about another platform is drawn from a page that platform publishes itself — its documentation, pricing page, terms or acceptable use policy. We link them all at the bottom of each page.
- Nothing here comes from running their service. We compare published behaviour against published behaviour, which is the part you can verify without opening an account.
- Where a platform's own documents contradict each other, we quote both and say the contradiction is unresolved rather than choosing the reading that suits us.
- Where a platform does something better than we do, that is what the row says. One of them publishes spend caps as detailed as ours, and that same platform publishes a contractual availability commitment where we publish only an operational target.
Platforms
The platforms we compare against
Picked because developers evaluate them against us in practice, and because each one publishes enough documentation to be compared honestly. Their focus lines are their own descriptions of themselves.
Replicate
Calls itself a way to run AI with an API — the broadest catalogue here, including community models anyone can publish.
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Runware
Calls itself one API for all AI — a single endpoint covering image, video, audio, 3D and text, priced pay-as-you-go.
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Segmind
Calls itself media generation workflows for developers — an API gateway plus a node-based workflow builder that publishes itself as an API.
See the comparison
OpenRouter
Calls itself the unified interface for every model — one API and one credit balance across 400+ models and their providers, text first, with image, video and speech endpoints alongside.
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Together AI
Calls itself the AI native cloud — open-model inference, GPU clusters and training, with image and video as one category among many.
See the comparisonWhat actually differs
The four differences that change your integration
The same model name does not guarantee the same defaults or output. Compare version, references and settings first, then policy, billing, delivery and budget controls.
Content policy
What the platform will refuse, and who decides
Two different mechanisms get called content policy. One is contractual: what the terms or acceptable use policy forbid you to generate. The other is operational: a moderation layer or safety-checker parameter sitting in front of the model. A platform can be permissive in one and strict in the other, and only reading both tells you which requests will actually complete.
No per-request content review, no safety-checker parameter to negotiate and no content-mode flag on the key. What a model will or will not produce is decided by that model. Unlawful use stays prohibited by the acceptable use policy and the reporting channel is public.
How you are billed
What one unit of billing actually is
Compare the unit before the headline price: images, megapixels, output seconds, tokens and GPU-seconds measure different things. Include output count, references and any subscription or credit-purchase fees in your workload total.
US dollars, per the unit the task itself is measured in. No credit currency to convert, no subscription, no plan tier, no monthly minimum. A quote call prices the exact body you are about to send and reserves nothing. Balance is topped up by card or crypto (USDT).
Request shape
What the HTTP response means
Media generation outlives the request that starts it. Whether the platform answers synchronously, hands you a job ID to poll, or calls you back decides how your queue, your retries and your timeouts are built — and that is the part of an integration that is expensive to change later.
One create call answers 202 with a task ID; results arrive by polling or by signed webhook. Text speaks an OpenAI-compatible surface on the same key. Input is validated against a published schema with additionalProperties closed, and every write accepts an Idempotency-Key for 24 hours.
Spend controls
What stops a loop that has gone wrong
A leaked key and a retry loop cost the same thing: whatever the platform lets them spend before something says no. A prepaid balance is a floor, not a control — it stops the spend only after the money is gone. A cap that is decided when the task is admitted stops it before.
Set daily, monthly and lifetime spending caps on each key. New keys have no spending cap until you set one. You can also restrict a key to selected models and source IP addresses; unsettled holds count toward its allowance.
Side by side
Every platform, on the two rows people ask about first
Content policy and spend controls decide most evaluations. The full eight-row table for each platform is on its own page.
| Platform | Built around | Content policy | Spend controls |
|---|---|---|---|
| SpicyAPI | Uncensored generative media and OpenAI-compatible text on one key, priced in US dollars per the unit each task is measured in. | No per-request content review, no safety-checker parameter to negotiate and no content-mode flag on the key. What a model will or will not produce is decided by that model. Unlawful use stays prohibited by the acceptable use policy and the reporting channel is public. | Set daily, monthly and lifetime spending caps on each key. New keys have no spending cap until you set one. You can also restrict a key to selected models and source IP addresses; unsettled holds count toward its allowance. |
| fal.ai | Calls itself a generative media platform for developers — queue-first image, video and audio APIs with a large first-party catalogue. | An acceptable use policy with specific prohibitions, plus an automated moderation API integrated platform-wide. Image endpoints take enable_safety_checker, which defaults to true; disabling it requires account authorization, and unauthorized requests are always checked, with flagged images returned as black frames. | No per-key or monthly spend cap appears in the public documentation. The account locks when the credit balance falls below a threshold, and concurrency limits bound throughput rather than spend. |
| Replicate | Calls itself a way to run AI with an API — the broadest catalogue here, including community models anyone can publish. | The terms state in capitals that the service can generate objectionable content and that the output is the customer's to manage. The acceptable use policy addresses content only as a general prohibition on obscene or offensive material. A safety checker runs on certain base models and their fine-tunes for web predictions; a disable_safety_checker parameter defaults to false and is documented as API-only. | The ability to set a monthly spend limit was deprecated, with the changelog directing customers who need it to contact support. What remains is the prepaid balance, which stops new work once it reaches zero, and a reload threshold. No per-key limit is documented. |
| Runware | Calls itself one API for all AI — a single endpoint covering image, video, audio, 3D and text, priced pay-as-you-go. | The terms prohibit harmful material involving minors and age-inappropriate material targeting minors, and we found no clause restricting other uncensored content. A separate section makes the customer responsible for age verification and access controls, and states the platform provides no consumer-facing age verification. Safety checking is an opt-in boolean and also a separately callable model; the response carries a content flag rather than refusing. | No spend cap, daily budget or per-key limit appears in the public documentation. What is documented is a prepaid balance, a reload threshold and low-balance alerts, plus read-only usage reporting that can be filtered by key. |
| Segmind | Calls itself media generation workflows for developers — an API gateway plus a node-based workflow builder that publishes itself as an API. | Its published acceptable use terms contain no clause specific to uncensored content, addressing only unlawful use and third-party rights. Its own blog states that the master agreement prohibits unfiltered generation, and we could not find that clause in the agreement text. A separate post markets a video model as available with no extra moderation layer. Models expose an upstream tolerance setting rather than an off switch, and a blocked request returns HTTP 422. | Stronger than ours in one respect: team workspaces set a daily, weekly and monthly dollar cap per member, any period optional, and a request that hits one returns an error naming the period and the cap. A workspace-wide model blocklist is also available. Caps do not apply to the workspace owner. |
| OpenRouter | Calls itself the unified interface for every model — one API and one credit balance across 400+ models and their providers, text first, with image, video and speech endpoints alongside. | The terms carry no general clause on uncensored content. They prohibit illegal use and child sexual abuse material, and require you to comply with each model's own terms, which differ by provider and flow down to your users. Operationally, the models API flags whether a provider applies moderation, filter blocks and model refusals come back as HTTP 403, and the terms let OpenRouter screen or block inputs it judges objectionable. Jailbreaking a model without written approval is prohibited. | Each key takes one credit limit that can reset daily, weekly or monthly at midnight UTC, or never; the documented error when it runs out is 402. Guardrails add a USD budget with its own reset plus model and provider allowlists, assigned per key and per organisation member, and the lower limit wins. Workspace budgets with up to four intervals, including lifetime, are available on the Enterprise plan. |
| Together AI | Calls itself the AI native cloud — open-model inference, GPU clusters and training, with image and video as one category among many. | No separate acceptable use policy document; the restriction lives in the terms of service, which prohibit using the service to communicate material that is obscene, alongside a right to suspend access for breach. Image generation exposes a disable_safety_checker parameter, documented as running by default and returning HTTP 422 when triggered. | A maximum monthly spending limit exists at account level — the 402 error code names it — but we found no documentation for setting or adjusting it, and none for a per-key budget. Documented usage limits are dynamic rate limits rather than spend. |
Swipe horizontally to see all columns.
Compare the documented model, billing and budget controls; use the linked sources for the details that affect your workload.
Models
Models you can call for this
Each link opens that model family's own page: inputs, limits, content policy and the current price per unit.
AlibabaWan 3.0Text to videoContent policy: UncensoredByteDanceSeedream 5.0 ProText to imageContent policy: UncensoredByteDanceSeedance 2.5 SpicyImage to videoContent policy: UncensoredAlibabaQwen Image 2.1Image editingContent policy: UncensoredxAIGrok 4.7ChatContent policy: UncensoredByteDanceSeedance 2.5Text to videoContent policy: Uncensored
FAQ
About these comparisons
These comparisons are published by SpicyAPI. Official sources are linked, and the pages identify useful competitor features, including Segmind's member budgets and enterprise availability commitment.
Use the chosen model's published rate card for competitor pricing and the model page or cost calculator for SpicyAPI. Match sizes, duration and output count; avoid comparing different billing units directly.
No. We compare published documentation against published documentation. Benchmarking someone else's service and publishing the result invites a fight about methodology that neither side can settle, and it would tell you about our test conditions rather than about your workload.
Because it is the row that cannot be worked around in code. A field name you can map and a billing unit you can convert, but a platform that refuses your request refuses it at every price. Most platforms compared here restrict unfiltered output in their terms or acceptable use policy; others restrict only content involving minors and leave the rest to the customer, or hand the question to the terms of each model they route to.
These are platform comparisons, not image-quality benchmarks. A shared model name can still hide different versions or defaults. Use the endpoint's settings and examples, then compare your own reference and prompt before migrating.
Next
Price the exact request before you move anything.
Every model page shows the required inputs, a runnable example and the cost for the settings you picked. Nothing is reserved until you submit.