Inkling-SmallThinking Machines Lab
|
MiMo-V2-FlashXiaomi Technology
|
|||||
Related Products
|
||||||
About
Inkling-Small is an efficient model that offers performance comparable to Inkling at a quarter of its size. It is a Mixture-of-Experts transformer with 276 billion total parameters and 12 billion active parameters, trained on NVIDIA GB300 NVL72 systems. It supports native reasoning across text, images, and audio, variable thinking effort, and context windows of up to one million tokens. Users adjust reasoning effort from minimal to extra high to balance performance and compute. Improved pre-training data, post-training with on-policy distillation from Inkling, and extended agentic coding reinforcement learning helped Inkling-Small surpass its larger counterpart on reasoning and coding benchmarks. It performs well in coding and tool-use harnesses, exceeds 80% on SWE-bench Verified, and combines strong reasoning with efficient output. Its encoder-free multimodal architecture processes audio as dMel spectrograms and images as 40-by-40-pixel patches alongside text tokens.
|
About
MiMo-V2-Flash is an open weight large language model developed by Xiaomi based on a Mixture-of-Experts (MoE) architecture that blends high performance with inference efficiency. It has 309 billion total parameters but activates only 15 billion active parameters per inference, letting it balance reasoning quality and computational efficiency while supporting extremely long context handling, for tasks like long-document understanding, code generation, and multi-step agent workflows. It incorporates a hybrid attention mechanism that interleaves sliding-window and global attention layers to reduce memory usage and maintain long-range comprehension, and it uses a Multi-Token Prediction (MTP) design that accelerates inference by processing batches of tokens in parallel. MiMo-V2-Flash delivers very fast generation speeds (up to ~150 tokens/second) and is optimized for agentic applications requiring sustained reasoning and multi-turn interactions.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Developers, AI agent builders, software engineering teams, research teams, enterprise AI teams, multimodal application developers, coding assistant builders, tool-use workflow teams, and organizations that need efficient reasoning, long-context processing, text-image-audio understanding, adjustable thinking effort, coding performance, and scalable Mixture-of-Experts inference
|
Audience
Developers and researchers requiring a solution to build high-performance AI applications involving long-context reasoning, coding, and agentic workflows
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Pros & Cons from Real UsersPros
Cons
|
||||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationThinking Machines Lab
Founded: 2025
United States
thinkingmachines.ai/news/inkling-small/
|
Company InformationXiaomi Technology
Founded: 2010
China
mimo.xiaomi.com/blog/mimo-v2-flash
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
|
|
||||||
Categories |
Categories |
|||||
Integrations
Claude Code
Hugging Face
Model Context Protocol (MCP)
Tinker
Xiaomi MiMo
Xiaomi MiMo Studio
|
Integrations
Claude Code
Hugging Face
Model Context Protocol (MCP)
Tinker
Xiaomi MiMo
Xiaomi MiMo Studio
|
|||||
|
|
|