July 22, 2026
How Thinking Machines Lab’s Inkling performs on agentic knowledge work
See model pageThinking Machines Lab’s Inkling scores an Elo of 836 on on our agentic knowledge work benchmark AA-Briefcase, ahead of DeepSeek V4 Flash but below leading open weights models including Nemotron 3 Ultra and GLM-5.2
Our new agentic knowledge work benchmark, AA-Briefcase, tests models on realistic tasks across thousands of input files, requiring deliverables such as spreadsheets, presentations, and UI mock-ups. Model performance is measured across three dimensions: binary rubric checks for ground-truth correctness, pairwise grading on analytical quality, and pairwise grading on presentation quality. The AA-Briefcase Elo is a single metric that combines results across all three dimensions
Key Takeaways:
➤ Scores 19.3% on the AA-Briefcase rubric, below MiMo-V2.5-Pro (21.4%) but above DeepSeek V4 Flash max (18.7%) and Gemini 3.5 Flash-Lite (14.8%). Inkling’s rubric score is worst on tasks which include non standard “Other” file types (i.e., not Excel, PowerPoint, PDF, or Word), despite its native multimodal support
➤ Performs higher on Presentation than Analytical Quality with Elo scores of 863 and 764 respectively. Presentation and Analytical Quality are both measured using separate, independent pairwise checks from model submissions. Graders compare two submissions for the same task and pick the one that is more professionally presented (Presentation) and the one with deeper, better-structured analysis (Analytical Quality)
➤ Uses 52K output tokens on average per AA-Briefcase task and 5M output tokens for the full suite, slightly more than models with similar scores on AA-Briefcase. Inkling uses the most tokens for Excel deliverables, followed by Word, PDF, PowerPoint, and Other types
➤ Has one of the highest mean turns per AA-Briefcase task (81) with also one of the widest ranges, resulting in a much lower median (49). Despite one of the higher average turns per task, Inkling comparatively uses fewer tool calls per turn on average (0.5)

Inkling scores 19.3% on the AA-Briefcase rubric, below MiMo-V2.5-Pro (21.4%) but above DeepSeek V4 Flash max (18.7%) and Gemini 3.5 Flash-Lite (14.8%)

Inkling performs higher on Presentation than Analytical Quality with Elo scores of 863 and 764 respectively

Inkling’s rubric score is worst on tasks which include non standard “Other” file types (i.e., not Excel, PowerPoint, PDF, or Word), despite its native multimodal support

Inkling uses 52K output tokens on average per AA-Briefcase task and 5M output tokens for the full suite, slightly more than models with similar scores on AA-Briefcase. Inkling uses the most tokens for Excel deliverables, followed by Word, PDF, PowerPoint, and Other types

Inkling has one of the highest mean turns per AA-Briefcase task (81) with also one of the widest ranges, resulting in a much lower median (49)

Despite one of the higher average turns per task, Inkling comparatively uses fewer tool calls per turn on average (0.5)

For more details: https://artificialanalysis.ai/evaluations/aa-briefcase
Read the latest

Agnes AI releases Agnes 2.5 Pro Beta
Agnes 2.5 Pro Beta
August 27, 2026

Intelligence at pocket scale: Benchmarking small models and mobile phones
Independent intelligence benchmarking of small language models on a set of evaluations chosen for mobile device use, launched alongside mobile phone inference benchmarking with Liquid AI. We evaluate the same quantized builds used on mobile phones, and performance is measured on real devices.
August 24, 2026

Announcing the Speech Agent Arena: Compare Speech agents in real world conversations
Announcing our new Speech Agent Arena, evaluating Speech to Speech models on real-world scenarios to analyze conversational preference and task success rate
August 24, 2026