Inkling
ThinkyMachines • LLM
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,...
Specifications
Context Window
1.0M tokens
Input Price/1M
$1.00
Output Price/1M
$4.05
Parameters
—
Speed
85 tok/s
Latency (TTFT)
1.8s
Max Output
262K tokens
Benchmarks
Inkling results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Coding Index | 52.1 | 100.0 | Artificial Analysis official API |
| SciCode | 46.0 | 100.0 | — |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 63.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 42.3 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 87.2 | 100.0 | Artificial Analysis official API |
| HLE | 30.0 | 100.0 | — |
Information
- Release date
- July 15, 2026
- Tool Calling
- ✅ Supported
- Vision
- ✅ Supported
- Audio
- ✅ Supported
Full Analysis: Inkling
What is Inkling?
Inkling is an AI model developed by ThinkyMachines, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via ThinkyMachines's cloud API. With a context window of 1.0M tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
Inkling is usage-based, priced at $1/1M input tokens and $4.05/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The mid-range pricing balances quality and cost for most professional applications.
Benchmarks & Performance
Inkling was evaluated on 6 different benchmarks, covering categories like Coding, Long Context, overall, Reasoning. Results show solid performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Inkling is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), image and visual document analysis (OCR, diagrams, screenshots), text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Inkling competes directly with similarly capable models. ThinkyMachines competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Inkling?
Inkling is an AI model developed by ThinkyMachines. It is a language model (LLM).
How much does Inkling cost?
Inkling costs $1/1M input tokens and $4.05/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Inkling compare with other models?
In available benchmarks, Inkling scored: AA Coding Index: 52.1/100, SciCode: 46/100, AA-LCR: 63/100. See the full table above for a detailed comparison.
Is Inkling open source?
No, Inkling is a proprietary model from ThinkyMachines. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is Inkling best for?
Inkling excels at multimodal tasks including text and vision. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: August 10, 2026 • View methodology →