Meet Keye-VL-2.0-30B-A3B — the latest 30B-class flagship base model in the Keye series, purpose-built to push the frontier of long-video understanding and to unlock the first generation of Agent capabilities in the Keye family.
Highlights
Video Benchmark Comparison
Outstanding Video Understanding and Temporal Localization: Across five video benchmarks, Keye-VL-2.0-30B-A3B leads open-source competitors and matches or surpasses Gemini-3-Flash on temporal grounding.
DSA-Native Long-Context Architecture: Sparse attention and targeted feature aggregation enable precise hour-long video understanding while keeping computation efficient.
High-Efficiency Inference and Training Stack: DSA (DeepSeek Sparse Attention), ExtraIO, heterogeneous ViT-LM parallelism, activation optimization, and custom kernels reduce long-sequence prefill cost and boost training throughput.
Data-Centric Multimodal Pre-Training: A carefully curated data pipeline, Keye-VL-1.5 vision encoder, and synthetic CoT data strengthen perception, OCR/chart/table understanding, and reasoning continuity.
Robust Post-Training for Reliable Reasoning: MOPD, bucket advantage scaling, Context-RL, and high-SNR data filtering improve cross-modal expert merging, reduce hallucinations, and stabilize long-context decisions.
Agent-Ready Multimodal Capabilities: Built-in Code, Tool, and Search agent abilities support repository tasks, API-style tool use, web-grounded search, and visual self-correction workflows.
As the first multi-modal model to land DSA in production, Keye-VL-2.0-30B-A3B delivers nearly lossless reasoning over 256K ultra-long context. It tops video understanding benchmarks at its scale and consistently rivals — or surpasses — top-tier closed-source models on fine-grained temporal perception. More importantly, it is the first Keye base model to ship with a built-in Agent collaboration mechanism, demonstrating solid system-level orchestration in Search, Tool, and Code scenarios.
Model Performance on Benchmarks
We compare Keye-VL-2.0-30B-A3B against leading open- and closed-source models (Qwen3.5-35B-A3B, InternVL3.5-241B-A28B, GPT-5-mini, Qwen3-VL 30B-A3B / 32B / 235B-A22B) across seven capability dimensions: Video, Coding, Agent, Math & Reasoning, STEM, Instruction Following, and General VQA.
Performance Comparison
Selected highlights (see the technical report for the full table):
Fine-grained Temporal Understanding (TimeLens):
Charades-TimeLens: 58.4 mIoU, on par with the strongest closed-source video baselines we tested (Gemini 3 Flash 61.19).
QVHighlights-TimeLens: 70.1 mIoU, neck-and-neck with the top closed-source models on the official leaderboard and far ahead of Gemini 3 Flash (49.45).
Long-Context Scaling (VideoMME V2): Where most competitors degrade as the input frame count grows, our model's accuracy increases from 35.3% at 64 frames to 42.4% at 512 frames; the non-linear reasoning score climbs from 18.5 to 24.2.
Comprehensive Long-Video Understanding:
LongVideoBench: 74.1, surpassing both Qwen3.5-35B-A3B and the much larger Qwen3-VL-235B-A22B, demonstrating strong long-video understanding at 30B scale.
At 30B scale, Keye-VL-2.0-30B-A3B not only outperforms open-source models with 200B+ parameters (e.g., Qwen3-VL-235B) on temporal understanding, but also goes head-to-head with — and in places exceeds — top closed-source giants.
