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Video understanding models take a whole video and answer questions about it, reasoning across time instead of generating footage. The hard part: scores swing with frame sampling and audio, and some models need frames extracted first. We ranked 14 by benchmark, price, and real access.

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Best Video Understanding Models

#ModelBest for

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How to Choose

When choosing between these models, consider:
  • Access: First decide whether you want an app, an API, or a model you run yourself, because that choice drives cost, privacy, latency, and setup work. Proprietary models are hosted only. Open weights split hard: GLM-4.6V Flash and SmolVLM2 2.2B run on a typical machine, Qwen3.5 27B and Gemma 4 31B need a high-end one, and Kimi K2.5, MiMo V2.5, and Qwen3.5 397B are “open” but really need server infrastructure.
  • Quality: We use a normalized Video-MME-v2 score, averaging its with-subtitle/audio and without-subtitle/audio conditions. The benchmark runs 3,200 grouped questions across 800 videos and rewards consistent answers over a whole clip, not lucky single hits. A few scores are directional: Gemini 3.1 Pro and 3.5 Flash inherit a predecessor Gemini result, and MiMo V2.5, Qwen3.7 Plus, Pegasus 1.5, and SmolVLM2 2.2B use estimates from related benchmark or family evidence rather than a run of that exact model, so treat narrow gaps as ties. Frame count and audio or subtitle input also move scores, so a leaderboard number is a guide, not a guarantee.
  • Price: We compare USD per hour of source video, the cleanest way to line up hosted models. It measures one hour of footage, not equal visual detail - a model can look cheap because it samples fewer frames and inspects less. Several prices here are same-provider or third-party estimates rather than firm quotes, so confirm live rates before you budget.
  • Video support: All 14 picks accept a video file directly through their listed route. The frame-based models we mention below need you to extract and order frames yourself first, a real extra step. Audio-included models read the embedded track in one call; audio-separate models need your own transcription pipeline; and duration limits range from one minute (Gemma 4 31B) to three hours (Gemini).

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Other Models We Considered

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Frequently Asked Questions

Gemini 3.1 Pro. It reads long footage and its audio together and handles up to three hours in one request. Its score uses the earlier Gemini 3 Pro benchmark result, while Doubao Seed 2.0 Pro is the strongest directly measured current model and costs far less.
Gemini 3.5 Flash. You get the same direct video-and-audio workflow as 3.1 Pro, faster and much cheaper, with only a small quality drop. Test it against Doubao Seed 2.0 Pro on your own footage, since that pairing covers most hosted use at a sensible price.
Qwen3.5 397B A17B has the highest measured open score, but it is server-only. Kimi K2.5 is the easiest to actually use, with a first-party app and API on top of its weights. If you need the embedded audio track read in one model, MiMo V2.5 is the standout open pick.
On a typical machine, GLM-4.6V Flash and SmolVLM2 2.2B are the realistic options - GLM for more capability, SmolVLM2 for the lightest laptop footprint. With a high-end GPU, Qwen3.5 27B is meaningfully stronger, while Gemma 4 31B and Qwen3.6 35B A3B suit short clips and efficient self-hosting respectively.
Gemini 3.1 Pro, Gemini 3.5 Flash, Doubao Seed 2.0 Pro, MiMo V2.5, Qwen3.5 Omni Plus, and Pegasus 1.5 read the embedded audio track directly. The other Qwen checkpoints, Gemma 4 31B, GLM-4.6V Flash, and SmolVLM2 2.2B handle only visuals, so you supply speech through a separate transcription step.
No. Products like video indexers and search platforms often wrap a model in retrieval, OCR, and transcription. This list ranks the models themselves. Pegasus 1.5 is a genuine model, not a platform, but reach for a retrieval pipeline when useful moments are sparse across many hours of footage.
Roughly. They predict which models reason across time and handle long clips, but results shift with frame count, audio input, prompting, and each provider’s own preprocessing. Some scores here are estimates or predecessor proxies. Treat close rankings as ties and run a short test on your own videos before committing.
Three things: how you want to access it (app, API, or self-hosted), how long your videos are and whether audio matters, and your tolerance for cost versus quality. Match the model to your longest, messiest real footage, because that is where the differences show up.