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The headline feature: send a single prompt to N models and get all results in one structured response. No more juggling Replicate, OpenAI, Runway, ElevenLabs, and a dozen other dashboards to find which model handles your use case best. Rimp spans 8 modalities behind one API key and one credit balance:
Costs below are in credits — Rimp’s universal currency (≈ 1,000 credits per $1 of underlying provider cost). The figures are the base cost per unit, exactly as shown in Studio; your wallet debit then applies your plan’s margin multiplier (Free ×1, Pro & Studio ×1.6, Team ×1.3). Call GET /v1/models for the live catalog. cr = credits.
Models tagged Studio+ require a Studio or Team plan. Calling them on Free or Pro returns 402 plan_upgrade_required.

Image models

Video models

Billed per second unless noted. Image-to-video models accept an image_url.

Voice models

Music models

Avatar models

Billed per second of output. Two request shapes: text-to-avatar (text + optional avatar_id/voice_id) or lipsync (video_url + audio_url).

3D models

Output is a GLB mesh URL. Billed per mesh.

Upscale models

Chat models

Billed per output token. The figures below are credits per 1M output tokens — a single turn typically uses far fewer (the default cap is 1,024 tokens). Charged on max_tokens, then reconciled with actual usage on completion.

Comparison API

Send one prompt to several models at once. Works across any models that share a modality.

Atomic credit reservation

Rimp sums the estimated cost of all N models and reserves it in one transaction. If your wallet can’t cover the sum, you get 402 Insufficient credits and nothing is charged — not even the models that would have fit.

Plan limits

The number of models per comparison is capped by your plan:

Polling vs webhooks

A comparison returns 202 with a parent comparison object. Two ways to wait for results:
Fetch the full result any time with GET /v1/comparisons/{id} — it returns the parent plus every child generation (status, charged credits, and signed output URLs).

Capability matrix

Not every model supports every operation. Check the capabilities array on each model (visible in the tables above and in GET /v1/models):
Common capabilities: text_to_image, image_to_image, text_to_video, image_to_video, text_to_voice, voice_clone, transcription, text_to_music, lipsync, text_to_text, tool_use, multimodal_input, text_to_3d, image_to_3d, rigged_3d, image_upscale, face_restore.