Model library

ResetData's serverless catalogue offers leading open-weight models with high-speed inferencing, hosted entirely on sovereign Australian infrastructure.


Available models at a glance

Model Provider Type Architecture Context Licence Best for
Z.ai GLM 5.2zai/glm-5.2 Z.ai (Zhipu AI) Text, reasoning MoE: 753B total, 8 of 256 experts active per token 800K tokens MIT Complex reasoning, long-horizon agentic work, bilingual English/Mandarin
Gemma 4 26B A4B Instructgoogle/gemma-4-26b-a4b-it Google DeepMind Text, image and video input MoE: 26B total, ~4B active per token 256K tokens Gemma Terms of Use Long documents, RAG, document and image understanding, regulated data
Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct Alibaba Text, code MoE: 30B total, ~3B active per token 256K tokens (1M with YaRN) Apache 2.0 Agentic coding at repository scale
Whisper Large V3 Turboopenai/whisper-large-v3-turbo OpenAI Speech to text Speech recognition model Audio input MIT Transcription, meeting notes, subtitles, translation to English

Pricing

All models are billed per token in AUD. Current per-model rates are listed in our model catalog.

About the models

Z.ai GLM 5.2

For hard problems where reasoning quality justifies a higher cost per query.

Capabilities

  • Long-horizon reasoning with adjustable effort

  • Advanced coding, agentic engineering and tool use

  • Mathematical reasoning and problem-solving

  • Native, high-fidelity English and Mandarin, suited to organisations operating across APAC

  • FP8 weights with sparse attention for efficient serving

Use cases:

Chat, reasoning, code generation, agentic tasks, tool use, long-context analysis and bilingual tasks.

Gemma 4 26B A4B Instruct

Delivers near-dense quality at a fraction of the inference cost. Structured thinking mode, and a built-in function-call protocol. Accepts text, images and video.

Capabilities:

  • MoE architecture (26B total / ~4B active per token)

  • Vision input: up to 4 images per request

  • Video input: 1 clip per request, up to 60 seconds at 1 fps

  • Structured thinking mode for reasoning

  • Function calling and tool use

  • Multilingual support

  • Instruction-tuned for chat and tool-augmented workflows

Use cases:

Chat, reasoning, tool use, code generation, long-context analysis, multilingual support, question answering, image analysis, video analysis and document understanding.

Qwen3 Coder 30B A3B Instruct

Purpose-built for agentic and repository-level coding workflows. No thinking-mode tokens - direct response generation.

Capabilities:

  • Agentic coding at repository scale

  • Function calling and tool use (qwen3_coder parser format)

  • Multi-file refactoring, test generation and debugging

  • MoE architecture for fast decode (~3B parameters active per token)

Use cases:

Code generation, code completion, agentic coding, repository-level tasks, test generation, debugging, refactoring and tool use.

Whisper Large V3 Turbo

OpenAI Whisper Large V3 Turbo - faster variant of Whisper Large V3 with near-identical quality. Served via speaches (faster-whisper/CTranslate2). Supports MP3, WAV, FLAC, OGG, M4A.

Capabilities:

  • Automatic speech recognition in 99+ languages

  • Automatic language detection (language=multi)

  • Translation to English

  • MP3, WAV, FLAC, OGG/Opus and M4A input

  • Faster inference than Large V3 with minimal quality loss

Use cases:

Transcription, speech-to-text, meeting notes, subtitles, real-time transcription and translation.

Frequently asked questions

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