TimeLens-8B-GGUF

TimeLens-8B-GGUF

TimeLens-8B from TencentARC is an 8B-parameter multimodal vision-language model fine-tuned from Qwen3-VL-8B-Instruct using a novel RLVR (reinforcement learning with verifiable rewards) recipe on the high-quality TimeLens-100K VTG dataset, achieving state-of-the-art video temporal grounding performance among open-source models with 72.0% [email protected] (Charades-TimeLens), 64.5% [email protected] (ActivityNet-TimeLens), and 75.6% [email protected] (QVHighlights-TimeLens), significantly outperforming baselines like Qwen3-VL-8B-Instruct and Qwen2.5-VL-7B. Designed for precise localization of visual events described by natural language queries, it outputs timestamped segments in the format "The event happens in <start time> - <end time> seconds" using low FPS=2 sampling (min_pixels=642828, total_pixels=143362828) for efficient video processing via Transformers with Flash-Attention-2 support. Released with code, project page, and TimeLens-Bench evaluation suite, it excels on Charades-TimeLens, ActivityNet-TimeLens, and QVHighlights-TimeLens leaderboards for research in video understanding, temporal reasoning, and event detection.

TimeLens-8B [GGUF]

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):