Changelog

Full Audio API Support

Apertis now supports the OpenAI-compatible Audio API. Use a single API key to access leading TTS (text-to-speech) and STT (speech-to-text) models across providers.

Supported Models

Text-to-Speech (TTS)

• gemini-3.1-flash-tts-preview — Google's latest Flash TTS preview
• gpt-4o-mini-tts — OpenAI's lightweight real-time speech synthesis

Speech-to-Text (STT)

• gpt-4o-transcribe — Flagship high-accuracy transcription
• gpt-4o-mini-transcribe — Cost-efficient real-time transcription
• whisper-large-v3-turbo — Accelerated Whisper v3
• whisper-large-v3 — Full-precision Whisper
• whisper-1 — The classic, battle-tested baseline

Endpoints

Drop-in compatible with the OpenAI SDK — no code changes required:

• POST /v1/audio/speech — text → audio
• POST /v1/audio/transcriptions — audio → text
• POST /v1/audio/translations — audio → translated text

Billing

• PAYG (pay-as-you-go): shares the same quota balance as chat/completions
• Per-dimension billing: priced separately on input tokens / output

tokens / audio seconds, with admin-tunable AudioRatio

• File limit: 25 MB per multipart upload
• Subscriptions: audio models are PAYG-only for now (not included

in subscription plans)

Example

  from openai import OpenAI

  client = OpenAI(
      api_key="sk-your-apertis-key",
      base_url="https://api.apertis.ai/v1"
  )

  # TTS
  speech = client.audio.speech.create(
      model="gpt-4o-mini-tts",
      voice="alloy",
      input="Hello from Apertis."
  )
  speech.stream_to_file("hello.mp3")

  # STT
  with open("audio.mp3", "rb") as f:
      transcript = client.audio.transcriptions.create(
          model="whisper-large-v3-turbo",
          file=f
      )
  print(transcript.text)

Model Detail Page Updates

• Endpoint and code samples auto-switch based on the model's task
• TTS models now emit ready-to-run OpenAI SDK Python snippets
• Web Search pricing column hidden for voice models (:web is unsupported)

Grok 4.3

Grok 4.3 is a reasoning-focused model from xAI designed for agentic workflows, instruction following, and high factual accuracy tasks. It supports text and image inputs with text output, with reasoning always active and not configurable by effort level.

The model features a 1M-token context window with effectively no output token limit, making it well suited for long-document analysis, deep research, and multi-step agentic workflows. It uses tiered pricing, with higher rates applied to requests exceeding 200K total tokens.

Enjoy it.