/v1/models
Model catalog with the details needed to choose
Each row identifies a public model and its documented request capabilities.
10 models
MiMo-V2.6-Flash
mimo-v2.6-flashMiMo-V2.6-Flash is an open-source foundation model developed by Xiaomi. Built on a Mixture-of-Experts architecture with 309B total parameters and 15B activated per token, it employs a hybrid attention mechanism for...
- Provider
- Xiaomi
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 11.70
- Output RUB / 1M
- 23.40
MiMo-V2.6-Pro
mimo-v2.6-proMiMo-V2.6-Pro is the flagship foundation model developed by Xiaomi. Built at a scale of over 1T parameters, it is designed to push the ceiling of capability for the most demanding...
- Provider
- Xiaomi
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 36.35
- Output RUB / 1M
- 72.70
Gemini 3.8 Flash
gemini-3.8-flashGemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.
- Provider
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 62.67
- Output RUB / 1M
- 313.35
Google: Gemini 2.5 Flash
gemini-2.5-flashGemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater...
- Provider
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 25.07
- Output RUB / 1M
- 208.90
Google: Gemini 2.5 Flash Lite
gemini-2.5-flash-liteGemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...
- Provider
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 8.36
- Output RUB / 1M
- 33.42
Google: Gemini 3 Flash Preview
gemini-3-flash-previewGemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool...
- Provider
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 41.78
- Output RUB / 1M
- 250.68
Google: Gemini 3.1 Flash Lite
gemini-3.1-flash-liteGemini 3.1 Flash Lite is Google’s GA high-efficiency multimodal model optimized for low-latency, high-volume workloads. It supports text, image, video, audio, and PDF inputs, and is designed for lightweight agentic...
- Provider
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 20.89
- Output RUB / 1M
- 125.34
Google: Gemini 3.1 Pro Preview
gemini-3.1-pro-previewGemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...
- Provider
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 167.12
- Output RUB / 1M
- 1,002.71
Google: Gemini 3.5 Flash
gemini-3.5-flashGemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...
- Provider
- Context
- 1.05M
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 125.34
- Output RUB / 1M
- 752.03
Xiaomi: MiMo-V2.5
mimo-v2.5MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...
- Provider
- Xiaomi
- Context
- 262.14K
- Capabilities
- Text · Transcription
- Catalog updated
- Input RUB / 1M
- 11.70
- Output RUB / 1M
- 23.40
From catalog to request
Move from a public model ID to a visible request path
Create a key in the cabinet, point a compatible client to the endpoint, then choose a public model from this catalog. Usage and published pricing stay visible alongside the work.
- 01Create a platform API key.
- 02Set the compatible endpoint.
- 03Choose a public model ID.
- 04Review usage and pricing.
- Data source
- Live public catalog
- Catalog updated
Choosing and using models
Use the live catalog for availability and request capabilities.
Check its unavailable reason in the current catalog. Personal and shared workspaces can follow different access rules.
Use the public catalog or model discovery. Model IDs and availability can change, so avoid relying on an old list.
Review the selected model’s published modalities, limits, and supported request parameters before sending a request.
Start with the required modality and capability, then compare current context, limits, availability, and price.