Changelog

Claude Opus 4.7 (Fast)

Fast version of Claude Opus 4.7 is live.

Enjoy it.

What changed

• Added a Recent Availability card to model detail pages.
• Added heartbeat bars for the recent delivery window.
• Added hover and keyboard-focus tooltips with date, time, availability percentage, and status.
• Counted retried or fallback-routed requests as healthy when the request ultimately succeeds.

How to read it

The card reports observed delivery, not a synthetic uptime probe.

If Apertis has recent successful delivery for a model, the relevant heartbeat bucket is green. If an actual delivery failure is observed, the bucket can move to degraded or unavailable based on the observed success rate.

When there is no recent traffic for a bucket, Apertis treats that silence as no observed anomaly and displays it as green 100%. This keeps the signal aligned with the rule that a model should not look unhealthy just because no one called it during that interval.

Why this matters

You can now check model-level health from the same page where you review pricing, context, endpoints, and examples. Teams choosing between models can see recent delivery quality without waiting for a separate status page or paying for active probes.

The implementation stays cost-aware by using delivery results Apertis already sees during normal routing.

Enjoy it.

Mistral Medium 3.5

Mistral Medium 3.5 is a 128B dense instruction-following model from Mistral AI, supporting text and image inputs with text output. It is designed for agentic workflows, coding, and complex multi-step reasoning, with strong reliability in multi-tool orchestration and long-horizon tasks.

The model features a 256K token context window, configurable reasoning effort per request, and a custom vision encoder that handles variable image sizes and aspect ratios. With support for self-hosting on as few as four GPUs and availability under open weights, it is well suited for scalable, production-grade deployments.

Cobuddy

CoBuddy is a code generation model from Baidu, optimized for coding tasks and AI agent workflows. It delivers high inference throughput and low end-to-end latency, making it well suited for responsive development and automation environments.

The model includes native support for tool calling and reasoning, runs with FP8 quantization for efficient deployment, and supports a 131K token context window with up to 65K output tokens, enabling long-context coding and multi-step agentic workflows.

Enjoy them.

Apertis has received a broad UI/UX refresh across public pages, model browsing, API key selection, and admin workflows. This update focuses on a cleaner visual system, clearer product navigation, and more practical operational screens for daily use.

Highlights

• Refreshed the public experience with a redesigned 404 page, improved layout chrome, and a more polished route diagnostic view.
• Introduced the new Verbatim landing experience, including updated positioning, product sections, code preview, and lead capture flow.
• Added a signed-in Dashboard shortcut in the header for faster access to the main workspace.
• Redesigned the chat API key selection modal with a cleaner Apertis-style layout, clearer selection states, and improved preview coverage.
• Improved model detail pages with task-driven endpoint selection, better TTS examples, and cleaner handling of voice and web-search pricing states.
• Refined the model filter sidebar so empty task categories are hidden, making model discovery easier to scan.

overview card.

• Shared FAQ row styling across pages for a more consistent Apertis UI system.
• Cleaned up footer navigation and naming, including the updated Verbatim label.

User Experience

The new look reduces visual clutter, improves spacing consistency, and makes important actions easier to find.

Public pages now feel more aligned with the Apertis brand, while authenticated workflows are more direct and data-focused.

Quality

This refresh includes focused test coverage for updated components and route behavior, including header navigation, modal behavior, layout chrome, pricing helpers, filter behavior, and cost analytics logic.

Enjoy them.

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)