{"slug": "thinking-machines-releases-inkling-2-small-scores-31-on-ai-index", "title": "Thinking Machines releases Inkling 2 Small, scores 31 on AI Index", "summary": "Thinking Machines Lab released Inkling 2 Small on November 5, 2026, a Mixture-of-Experts model with 594 billion total parameters and 17 billion active, scoring 31 on the Artificial Analysis Intelligence Index (v5.0). The model ships as a closed-weight product on Thinking Machines' Tinker platform at $0.30 per 1 million input tokens and $1.00 per 1 million output tokens, with weights promised under an Apache 2.0 license after external safety testing and no date attached. Inkling 2 Small ranked 4th overall and 1st among open-weights models on DesignArena, and it more than doubles the total size of the July 30, 2026 Inkling-Small while raising active parameters from 12 billion to 17 billion.", "body_md": "# Thinking Machines releases Inkling 2 Small, scores 31 on AI Index\n\nThe lab's second-generation model launches with closed weights on Tinker, with an Apache 2.0 release planned after external safety testing\n\n[Thinking Machines Lab](https://cryptobriefing.com/markets/thinking-machines/) has released Inkling 2 Small, the newest member of its model family. It scored 31 on the Artificial Analysis Intelligence Index (v5.0).\n\nThe company calls itself committed to open weights. For now, though, the model ships as a proprietary product, with the weights promised later.\n\nThe launch landed on November 5, 2026. It is the lab’s second-generation release, arriving less than four months after the original Inkling lineup debuted in July.\n\n## What’s under the hood\n\nInkling 2 Small uses a Mixture-of-Experts architecture. It has 594 billion total parameters, but only 17 billion are active at any given time.\n\nEach request gets routed to a small subset of the model’s internal “experts.” The result is a model that holds a lot of knowledge but only spends a fraction of its compute on any single query.\n\nUsage through Thinking Machines’ Tinker platform costs **$0.30 per 1 million input tokens and $1.00 per 1 million output tokens**. The research findings describe that pricing as competitive with peers.\n\nThe model accepts image inputs and supports variable thinking effort. Users can dial up how hard it reasons on a problem, trading speed and cost for depth.\n\nThinking Machines is pitching it for agentic coding, vision, reasoning, and knowledge-work tasks. “Agentic” means the model can carry out multistep jobs on its own rather than simply answering one question at a time.\n\nTraining leaned on a large integrated reinforcement-learning run. That process lets the model use visual feedback to adjust its work in tasks like building websites and games.\n\n### AI, tech, and the markets they move—in one daily briefing.\n\nDaily. Free. Join 34,000+ readers across crypto, finance, and policy.\n\nOn benchmarks, Inkling 2 Small ranked 4th overall on DesignArena. It also placed 1st among open-weights models on that leaderboard.\n\nIts AA Intelligence Index score of 31 gives a single-number snapshot of general capability. The index is version 5.0, so the score reflects the latest edition of that test suite.\n\n## How it got here\n\nThinking Machines Lab launched in February 2025 with a $2 billion seed round at a $12 billion valuation.\n\nThe first Inkling model arrived on July 15, 2026. It was a larger system, with 975 billion total parameters and 41 billion active.\n\nInkling-Small followed on July 30, 2026, with 276 billion total parameters and 12 billion active. The new release sits between those two in size.\n\nInkling 2 Small is more than twice the total size of its namesake predecessor. Its active parameter count rose from 12 billion to 17 billion.\n\n## What this means\n\nThe most interesting tension is the weights question. Thinking Machines frames itself around an open-weights approach, yet Inkling 2 Small currently runs only as a closed model on Tinker.\n\nThe company plans to release the weights under an Apache 2.0 license after external safety testing. Apache 2.0 is a permissive license that generally lets anyone use, modify, and build commercial products on the software.\n\nUntil that release happens, developers can only access the model through Thinking Machines’ own platform. They can run inference and fine-tune it there, but they cannot download it and host it themselves.\n\nNo date has been attached to the weights release.\n\nAt $0.30 and $1.00 per million input and output tokens, the model targets teams that want strong coding and design capability without premium-tier bills.\n\nThe DesignArena results reinforce that pitch. A 4th-place overall finish, combined with the top spot among open-weights models, suggests the visual feedback training is paying off in front-end and design work.\n\n**Disclosure:** This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our [Editorial Policy](https://cryptobriefing.com/editorial-policy/).", "url": "https://wpnews.pro/news/thinking-machines-releases-inkling-2-small-scores-31-on-ai-index", "canonical_source": "https://cryptobriefing.com/thinking-machines-inkling-2-small-release/", "published_at": "2026-11-05 23:58:22+00:00", "updated_at": "2026-11-06 00:20:53.466890+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-products", "ai-startups", "ai-tools"], "entities": ["Thinking Machines Lab", "Inkling 2 Small", "Tinker", "Artificial Analysis Intelligence Index", "DesignArena", "Inkling-Small", "Apache 2.0"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/thinking-machines-releases-inkling-2-small-scores-31-on-ai-index", "markdown": "https://wpnews.pro/news/thinking-machines-releases-inkling-2-small-scores-31-on-ai-index.md", "text": "https://wpnews.pro/news/thinking-machines-releases-inkling-2-small-scores-31-on-ai-index.txt", "jsonld": "https://wpnews.pro/news/thinking-machines-releases-inkling-2-small-scores-31-on-ai-index.jsonld"}}