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84,736 model profiles13040 providers / publishers45 capability categories464 with comparable prices · 30 benchmarked
TText generation▧Image generation▷Video generation⌘Code generation◖Speech synthesis♫Music generation⬡3D modeling▤Document analysis
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Inkling (free)

thinkingmachines

Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning, coding, agentic and tool-use systems,...

Text generationOpen weights
Input Text · Image · Audio→ Output Text
$0 / M input tokensOpenRouter · thinkingmachines/inkling:free
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Inkling-NVFP4

thinkingmachines

Inkling is a general-purpose multimodal model that accepts text, image and audio inputs and generates text outputs. It is intended for use in English and other languages, and across multiple coding languages. The model is designed to be used by developers building AI-powered applications, including agentic and tool-use systems, coding assistants, chatbots, and retrieval-augmented generation systems, and is suitable for general-purpose conversational use, instruction-following, and other natural language and multimodal tasks. It is released with open weights to support research, fine-tuning and integration into third-party products by downstream developers. **Languages:** English, with general multilingual capabilities across other languages. Try Inkling on the Tinker Playground or access via API using the Tinker Cookbook.

Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
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Inkling Small

thinkingmachines

Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...

Text generationOpen weights
Input Text · Image · Audio→ Output Text
$0.45 / M input tokensOpenRouter · thinkingmachines/inkling-small
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Inkling Small (free)

thinkingmachines

Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...

Text generationOpen weights
Input Text · Image · Audio→ Output Text
$0 / M input tokensOpenRouter · thinkingmachines/inkling-small:free
View details ↗

Inkling-Small-NVFP4

thinkingmachines

Inkling-Small is a general-purpose multimodal model that accepts text, image and audio inputs and generates text outputs. It is intended for use in English and other languages, and across multiple coding languages. The model is designed to be used by developers building AI-powered applications, including agentic and tool-use systems, coding assistants, chatbots, and retrieval-augmented generation systems, and is suitable for general-purpose conversational use, instruction-following, and other natural language and multimodal tasks. It is released with open weights to support research, fine-tuning and integration into third-party products by downstream developers. **Languages:** English, with general multilingual capabilities across other languages. Try Inkling-Small on the Tinker Playground or access via API using the Tinker Cookbook.

Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
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1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

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