deAPI runs open-weight image, video, audio and multimodal models on a decentralized GPU network. It doesn't replace OpenAI for LLM or reasoning work — it sits alongside, covering the media modalities OpenAI's first-party catalog doesn't ship and running open-source Whisper on a decentralized GPU pool.
Four structural differences between deAPI and OpenAI's first-party media stack — useful where closed weights, split billing or the modalities OpenAI doesn't ship get in the way.
OpenAI's gpt-image-1.x, sora-2, tts-1 and gpt-4o-mini-tts are closed checkpoints that run only inside OpenAI. Whisper is OpenAI's one open-source exception. deAPI runs open-weight models end-to-end (Flux family, Z-Image Turbo, open-source Whisper, open voice models) — the weights live publicly upstream, so the model itself is auditable and not locked inside a single vendor silo.
Every inference vendor — OpenAI and deAPI included — iterates its catalog. OpenAI has announced dall-e-3 and dall-e-2 shutdown on 2026-05-12, and older sora-2 snapshots on 2026-09-24. The difference: closed OpenAI models exist only inside OpenAI, while the open-weight models deAPI runs live publicly upstream — so if a specific version rotates out of the deAPI catalog, the weights themselves aren't deleted from the ecosystem.
On OpenAI, LLM calls meter in tokens, gpt-image in image tokens, Whisper per audio minute, TTS per character (gpt-4o-mini-tts token-based) and Sora per video second — several contracts across several endpoints. deAPI bills per output on a consumption basis (resolution × steps for image, duration for video/music, characters for TTS, and so on) with one account, one invoice, one API surface. The per-modality metric differs; the vendor relationship and response contract don't.
OpenAI runs inference on its own centralized cloud. deAPI sources GPU-seconds from a global pool of independent providers competing for inference work. This is where the Whisper case gets interesting — the same open-source Whisper Large V3 model OpenAI exposes as whisper-1, but on a different supply layer. See the live pricing page for current numbers.
You need a modality OpenAI simply doesn't ship — music generation, open-source text-to-music, a specific open-weight voice model, or source-agnostic video transcription (YouTube / Kick / Twitch / X URLs, not just file uploads).
Your product is multi-modality and you want one response shape covering image, video, speech and music, not several distinct OpenAI endpoints returning distinct schemas.
Compliance or procurement wants open weights — the ability to audit the model and avoid single-vendor lock-in on the underlying checkpoints. OpenAI's media catalog is open-weight for Whisper only; everything else is closed.
You want to run Whisper (the same open-source model OpenAI exposes as whisper-1) on a decentralized GPU pool instead of OpenAI's centralized cloud.
You want to swap a closed OpenAI image or TTS model for an open-weight flagship (Flux family, Z-Image Turbo, open voices) without rewriting the surrounding integration.
LLM or reasoning work — GPT-5, o-series, the Responses API, function calling, Assistants. deAPI's catalog today is media-only and does not host LLMs.
You specifically need the output of a closed OpenAI media model — gpt-image-1.x's rendering signature, sora-2 / sora-2-pro camera-control, or the dedicated diarization output of gpt-4o-transcribe-diarize.
Realtime voice-agent UX (bidirectional streaming voice) — OpenAI's realtime voice API is production-ready and not matched one-to-one on deAPI today.
Your stack already leans on the Responses / Assistants / Apps SDK ecosystem and the integration cost of staying inside it beats adding a second provider.
Enterprise procurement demands OpenAI's specific compliance posture — SOC 2 Type II, BAA availability, data-residency controls — and the spec literally names OpenAI.
Scoped to image, video, audio and multimodal workloads — not LLMs. Every claim verified against public product docs as of April 2026.
| Dimension | deAPI | OpenAI (media) |
|---|---|---|
| Core positioning | ✓ Open-weight media inference | Frontier LLM + closed-source first-party media |
| Model weights | ✓ Open-weight (auditable, public upstream) | Closed, OpenAI-hosted only (except whisper-1) |
| Media catalog | Flux_2_Klein_4B_BF16, ZImageTurbo_INT8, txt2video, img2video, Whisper Large V3 transcribe, txt2speech, txt2music, OCR, embeddings | gpt-image-1, gpt-image-1.5, gpt-image-1-mini, sora-2, sora-2-pro, whisper-1, gpt-4o-transcribe, gpt-4o-mini-transcribe, gpt-4o-transcribe-diarize, tts-1, tts-1-hd, gpt-4o-mini-tts · dall-e-3 & dall-e-2 shut down 2026-05-12 |
| Whisper (open-source) | = Whisper Large V3 on decentralized GPUs | whisper-1 on centralized cloud (same model family, different infrastructure) |
| Billing shape | ✓ Per output, one vendor (metric varies by modality — pixels × steps, seconds, characters…) | Per media endpoint: tokens (LLM, gpt-image, gpt-4o-mini-tts) / minute (Whisper) / character (tts-1 / tts-1-hd) / second (Sora) |
| GPU supply | ✓ Decentralized global pool | OpenAI-operated centralized cloud |
| Auth header format | = Bearer token | Bearer token (same — no header change in migration) |
| Custom model hosting / BYO weights | Curated catalog only | Not supported — OpenAI-hosted only |
| Fine-tuning (media models) | Not currently supported | Not available for image / video / TTS |
| Agent-friendly docs (llms.txt, MCP) | = First-party | First-party (parity — both ship llms.txt + MCP) |
| Free credits on signup | ✓ $5, no credit card | No standing signup offer for paid API access |
Both platforms iterate frequently — pricing numbers intentionally omitted and model availability can shift. Always verify current capabilities on each vendor's live docs.
On OpenAI, image, audio-in and audio-out each live on a different endpoint, with a different body and a different billing unit. On deAPI the three collapse onto one shape — same Authorization: Bearer, same request_id polling, same webhook payload. Three side-by-sides below, one per modality.
# OpenAI
POST /v1/images/generations
{
"model":"gpt-image-1",
"prompt":"Futuristic city…",
"size":"1024x1024"
}
# deAPI
POST /v1/client/txt2img
{
"model":"Flux_2_Klein_4B_BF16",
"prompt":"Futuristic city…",
"width":1536,"height":896,
"steps":4,"seed":42
}# OpenAI
POST /v1/audio/transcriptions
-F [email protected]
-F model=whisper-1
# also: gpt-4o-transcribe,
# gpt-4o-mini-transcribe,
# gpt-4o-transcribe-diarize
# deAPI (same Whisper family)
POST /v1/client/transcribe
{
"url":"https://youtube.com/..."
}
# or upload via multipart —
# same request_id polling.# OpenAI
POST /v1/audio/speech
{
"model":"gpt-4o-mini-tts",
"voice":"alloy",
"input":"Hello from deAPI"
}
# also: tts-1, tts-1-hd
# deAPI (open-weight voice)
POST /v1/client/txt2speech
{
"model":"<open-weight-voice>",
"prompt":"Hello from deAPI"
}
# Same Bearer. Same request_id.
# Same webhook contract.Authorization header on both sides is Bearer — nothing to rewrite in your HTTP client config. The diff is endpoint path, request body and billing shape.
gpt-image-1.x, sora-2 / sora-2-pro, tts-1, gpt-4o-mini-tts) and one open-source exception, whisper-1. deAPI is an open-weight media inference layer — image, video, audio, multimodal — on a decentralized GPU network. Both sides use Authorization: Bearer, so running them together is straightforward: OpenAI keeps the LLM work, deAPI handles the open-weight image / video / audio models OpenAI does not ship, plus Whisper on a decentralized GPU pool.
/v1/chat/completions or Responses API; media generation routes to deAPI's /v1/client/txt2img, /txt2video, /transcribe and friends. One call pattern per modality, no LLM billing mixed into the media meter.
Flux_2_Klein_4B_BF16 and ZImageTurbo_INT8 for image generation, plus open-source text-to-video and image-to-video models against one shared schema. gpt-image-1.x and sora-2 / sora-2-pro stay inside OpenAI — if your product demands a specific closed-model rendering signature, keep that endpoint on OpenAI and route other image / video work through deAPI. The contract on the open-weight side: comparable output quality for most production use cases, plus the underlying weights live publicly upstream — auditable and not locked inside a single vendor.
Authorization: Bearer, so the HTTP client config does not change. You remap the endpoint path and the request body: OpenAI's /v1/images/generations maps to deAPI /v1/client/txt2img; /v1/audio/transcriptions maps to /v1/client/transcribe; /v1/audio/speech maps to /v1/client/txt2speech. Response shape is unified across deAPI's modalities, so a single polling or webhook handler covers every endpoint. You can also keep both live and route per workload — the two do not conflict.
Whisper Large V3 — the same open-source Whisper family model OpenAI's whisper-1 is backed by — on its own transcribe endpoint, with source-agnostic ingest (YouTube / Kick / Twitch / X URLs, or direct upload) that OpenAI's transcription does not surface natively. TTS — yes, on open-weight voices. /v1/client/txt2speech runs open-weight voice models (with upload-based voice cloning and Voice Design too); OpenAI's closed tts-1, tts-1-hd and gpt-4o-mini-tts stay on OpenAI's side. Video — yes. deAPI ships txt2video and img2video against open-weight models; sora-2 / sora-2-pro stay on OpenAI.
gpt-5, o-series, the Responses API, Assistants, function calling, realtime voice agents) and any closed-media endpoint you actively depend on (gpt-image-1.x, sora-2, gpt-4o-transcribe-diarize). deAPI handles the open-weight media loop: txt2img, img2video, txt2video, txt2speech, txt2music and transcribe — on one Bearer token, one response contract and a decentralized GPU pool. Bonus on the deAPI side: source-agnostic video transcription (YouTube / Kick / Twitch / X URLs or direct upload), upload-based voice cloning, and open-weight checkpoints that live publicly upstream. Same Bearer on both sides keeps the client config identical.
$5 of free credits. No credit card. Keep OpenAI for the LLM work, plug deAPI in for open-weight image, video, TTS, music — and Whisper on decentralized GPUs.
Migration assistance available — talk to an engineer.