Inkling-Small

Inkling-Small

Thinking Machines Lab
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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.

About

Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.

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

Muse Spark 1.1 is best suited for developers, AI engineers, enterprises, agent builders, coding tool teams, research teams, and productivity-focused users that need a multimodal reasoning model for agentic workflows, coding, computer use, long-context tasks, tool orchestration, and advanced automation

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

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
features 4.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.0 / 5
design 5.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • Inkling-Small is really interesting from a developer’s point of view because it hits a sweet spot between serious model capability and practical deployability. A 276B-parameter model with only 12B active parameters per token is exactly the kind of architecture that makes sense if you care about cost, speed, and scaling real AI workflows. I also like that it is open weights under Apache 2.0. That makes it way more appealing for developers who want to fine-tune, inspect, customize, or build on top of the model without being completely locked into a closed API. The multimodal support is a big plus too. Being able to work with text, images, and audio inputs gives Inkling-Small a lot of room for developer tools, coding agents, support bots, document workflows, and internal automation.

Cons

  • The main downside is that “small” here is still not tiny. Even with only 12B active parameters, this is still a large open model that will require real infrastructure if you want to host it yourself. I would also want to test it deeply before making it the backbone of a production coding agent. The model card and early coverage look promising, but real developer workflows expose problems that benchmarks do not always catch: messy repos, flaky tests, weird dependencies, tool failures, and long multi-step tasks.

Pros & Cons from Real Users

Pros

  • Muse Spark 1.1 has been awesome for the way I actually build with AI: agents, coding workflows, tool calls, debugging loops, and messy real-world tasks that do not fit neatly into a single prompt. It feels much stronger than the first version when I need it to reason through code, work across multiple steps, understand context, and keep an agent moving without constantly falling apart. The multimodal side is also a big plus because being able to work with docs, screenshots, images, and other inputs makes it way more useful for building practical AI products.

Cons

  • It is still early, so I would not call it perfect yet. Like any advanced model, you still need good scaffolding, evals, guardrails, and monitoring if you are putting it into production agent workflows. I also want to see the API ecosystem, docs, examples, and integration patterns mature more, because those things matter a lot when you are building real agentic systems instead of just testing prompts.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Thinking Machines Lab
Founded: 2025
United States
thinkingmachines.ai/news/inkling-small/

Company Information

Meta
Founded: 2004
United States
meta.ai

Alternatives

Alternatives

Claude Fable 5

Claude Fable 5

Anthropic
Claude Mythos 5

Claude Mythos 5

Anthropic
Claude Opus 5

Claude Opus 5

Anthropic
Inkling

Inkling

Thinking Machines Lab

Categories

Categories

Integrations

Model Context Protocol (MCP)
.NET
C
C++
Codex CLI
HTML
Hermes Agent
Java
JavaScript
Kotlin
LangChain
Muse Image
Objective-C
OpenCode
PowerShell
Python
SQL
Solidity
Tinker
YAML

Integrations

Model Context Protocol (MCP)
.NET
C
C++
Codex CLI
HTML
Hermes Agent
Java
JavaScript
Kotlin
LangChain
Muse Image
Objective-C
OpenCode
PowerShell
Python
SQL
Solidity
Tinker
YAML
Claim Inkling-Small and update features and information
Claim Inkling-Small and update features and information
Claim Muse Spark 1.1 and update features and information
Claim Muse Spark 1.1 and update features and information