Inkling-SmallThinking Machines Lab
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SmolLM2Hugging Face
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Related Products
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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.
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About
SmolLM2 is a collection of state-of-the-art, compact language models developed for on-device applications. The models in this collection range from 1.7B parameters to smaller 360M and 135M versions, designed to perform efficiently even on less powerful hardware. These models excel in text generation tasks and are optimized for real-time, low-latency applications, providing high-quality results across various use cases, including content creation, coding assistance, and natural language processing. SmolLM2's flexibility makes it a suitable choice for developers looking to integrate powerful AI into mobile devices, edge computing, and other resource-constrained environments.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Supported
iPhone
Supported
iPad
Supported
Android
Supported
Chromebook
Not Supported
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Audience
AI researchers and developers seeking an efficient open-weight multimodal model for reasoning, agentic tasks, and lower-cost deployment
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Audience
Developers and AI enthusiasts looking to integrate compact, high-performance language models into mobile apps, edge computing systems, or other devices with limited processing power
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Not Supported
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API
Offers API
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
Free
Open source
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Pros & Cons from Real UsersPros
Cons
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationThinking Machines Lab
Founded: 2025
United States
thinkingmachines.ai/news/inkling-small/
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Company InformationHugging Face
Founded: 2016
United States
huggingface.co/collections/HuggingFaceTB/smollm2-6723884218bcda64b34d7db9
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
Hugging Face
Not Supported
Locally AI
Not Supported
Mirai
Not Supported
Model Context Protocol (MCP)
Supported
Private Mind
Not Supported
Runpod
Not Supported
Tinker
Supported
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Integrations
Hugging Face
Supported
Locally AI
Supported
Mirai
Supported
Model Context Protocol (MCP)
Not Supported
Private Mind
Supported
Runpod
Supported
Tinker
Not Supported
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