Changelog

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.

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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.

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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.

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Nemotron 3 Nano Omni (Free)

NVIDIA Nemotron 3 Nano Omni is an open 30B-A3B multimodal model designed as a perception and context sub-agent for enterprise agent systems. It supports text, image, video, and audio inputs with text output, enabling unified multimodal reasoning within a single inference loop. Built on a hybrid MoE Transformer–Mamba architecture with Conv3D video layers and Efficient Video Sampling (EVS), it delivers significantly improved efficiency for video reasoning—achieving ~2× higher throughput and 2.5× lower compute compared to separate pipelines.

With up to 300K context length and extended thinking support, it is well suited for scalable, multimodal agent workflows.

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