Inkling-Small
Mira Murati • LLM
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...
Specifications
Context Window
524K tokens
Input Price/1M
$0.30
Output Price/1M
$1.20
Parameters
—
Speed
132 tok/s
Latency (TTFT)
1.6s
Max Output
262K tokens
Benchmarks
Inkling-Small results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Coding Index | 52.9 | 100.0 | Artificial Analysis official API |
| SciCode | 49.0 | 100.0 | — |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 63.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 41.2 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 89.5 | 100.0 | Artificial Analysis official API |
| HLE | 32.0 | 100.0 | — |
Information
- Release date
- July 30, 2026
- Tool Calling
- ✅ Supported
- Vision
- ✅ Supported
- Audio
- ✅ Supported
Full Analysis: Inkling-Small
What is Inkling-Small?
Inkling-Small is an AI model developed by Mira Murati, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via Mira Murati's cloud API. With a context window of 524K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
Inkling-Small is usage-based, priced at $0.3/1M input tokens and $1.2/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
Inkling-Small 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-Small 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), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Inkling-Small competes directly with similarly capable models. Mira Murati 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-Small?
Inkling-Small is an AI model developed by Mira Murati. It is a language model (LLM).
How much does Inkling-Small cost?
Inkling-Small costs $0.3/1M input tokens and $1.2/1M 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-Small compare with other models?
In available benchmarks, Inkling-Small scored: AA Coding Index: 52.9/100, SciCode: 49/100, AA-LCR: 63/100. See the full table above for a detailed comparison.
Is Inkling-Small open source?
No, Inkling-Small is a proprietary model from Mira Murati. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is Inkling-Small best for?
Inkling-Small 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 →