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Jonas Kübler
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amazon/chronos-2
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Announcing Artificial Analysis Long Context Reasoning (AA-LCR), a new benchmark to evaluate long context performance through testing reasoning capabilities across multiple long documents (~100k tokens) The focus of AA-LCR is to replicate real knowledge work and reasoning tasks, testing capability critical to modern AI applications spanning document analysis, codebase understanding, and complex multi-step workflows. AA-LCR is 100 hard text-based questions that require reasoning across multiple real-world documents that represent ~100k input tokens. Questions are designed so answers cannot be directly found but must be reasoned from multiple information sources, with human testing verifying that each question requires genuine inference rather than retrieval. Key takeaways: ➤ Today’s leading models achieve ~70% accuracy: the top three places go to OpenAI o3 (69%), xAI Grok 4 (68%) and Qwen3 235B 2507 Thinking (67%) ➤👀 We also already have gpt-oss results! 120B performs close to o4-mini (high), in-line with OpenAI claims regarding model performance. We will be following up shortly with a Intelligence Index for the models. ➤ 100 hard text-based questions spanning 7 categories of documents (Company Reports, Industry Reports, Government Consultations, Academia, Legal, Marketing Materials and Survey Reports) ➤ ~100k tokens of input per question, requiring models to support a minimum 128K context window to score on this benchmark ➤ ~3M total unique input tokens spanning ~230 documents to run the benchmark (output tokens typically vary by model) We’re adding AA-LCR to the Artificial Analysis Intelligence Index, and taking the version number to v2.2. Artificial Analysis Intelligence Index v2.2 now includes: MMLU-Pro, GPQA Diamond, AIME 2025, IFBench, LiveCodeBench, SciCode and AA-LCR. Link to dataset: https://huggingface.co/datasets/ArtificialAnalysis/AA-LCR
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Qwen/Qwen3-Coder-30B-A3B-Instruct:
What does `max_window_layers` do?
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liked
a model
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amazon/chronos-2
Time Series Forecasting
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0.1B
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Updated
Nov 5
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3.98M
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109
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11 models
12 months ago
autogluon/chronos-t5-base
Time Series Forecasting
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0.2B
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Updated
Oct 30
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17.7k
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5
autogluon/chronos-t5-small
Time Series Forecasting
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46.2M
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Updated
Oct 30
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1.24k
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5
autogluon/chronos-t5-mini
Time Series Forecasting
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20.5M
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Updated
Oct 30
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54.4k
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5
autogluon/chronos-t5-large
Time Series Forecasting
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0.7B
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Updated
Oct 30
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32.1k
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6
autogluon/chronos-t5-tiny
Time Series Forecasting
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8.39M
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Oct 30
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26.9k
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12
autogluon/tabpfn-mix-1.0-regressor
Tabular Regression
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Nov 27, 2024
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258
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14
autogluon/tabpfn-mix-1.0-classifier
Tabular Classification
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Updated
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63k
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17
autogluon/chronos-bolt-base
Time Series Forecasting
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0.2B
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Updated
Oct 30
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4.49M
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35
autogluon/chronos-bolt-mini
Time Series Forecasting
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21.2M
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Oct 30
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336k
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8
autogluon/chronos-bolt-small
Time Series Forecasting
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47.7M
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Oct 30
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5.55M
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20
autogluon/chronos-bolt-tiny
Time Series Forecasting
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8.65M
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Oct 30
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385k
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13