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Short answer: about 1 in 9. The Oakgen AI Video Index 2026, based on 4,069 video generations on Oakgen from January 10 to November 10, 2026, found that 11.5% of jobs failed. More than a third of those failures were not bugs. They were content or copyright filters saying no.
That split matters. A server error is bad luck, and a retry often fixes it. A filter block is a decision, and a retry usually gets the same answer. Most wasted time on failed AI video comes from treating the second kind like the first.
The full dataset, with every number and its sample size, lives on the AI video statistics hub. This post explains the failure numbers in plain words.
Make a video with fewer surprises
Oakgen shows the model, the cost and the settings before you run a clip, and tells you which error code you hit if it fails.
How often do AI video generations fail?
The Oakgen AI Video Index 2026 counted 4,069 video jobs between January 10 and November 10, 2026.
- 88.4% of video jobs completed (n = 4,069).
- 11.5% of video jobs failed (n = 4,069).
- 6 jobs were still processing when the data was pulled.
- 467 jobs failed in total.
So for every nine videos you start, expect roughly one to come back with an error. That is an average across every model and mode. It hides a wide range.
Which kinds of AI video fail most?
Completion depends a lot on what you ask for. The same index split jobs by mode (decided by the inputs: any image or reference image counts as image-to-video, any input video counts as video-to-video).
- Text-to-video completed 93.4% of the time (n = 1,159).
- Image-to-video completed 87.3% of the time (n = 2,625).
- Video-to-video completed 77.9% of the time (n = 285).
- Trend videos, which turn your photo into a set scene, completed 62.1% of the time (n = 591).
Single models sit much higher. Kling v3 Pro text-to-video completed 98.1% of 207 jobs, and Grok text-to-video completed 98.3% of 116. See which AI video models people use for the full table.
The pattern is simple. The more of a real person or a real piece of media you put in, the more checks the request has to pass.
Why do AI video generations fail?
The index grouped the 467 failed jobs by their error code.
- 35.8% of failures were blocked by a content or copyright filter (n = 467).
- 24.4% of failures were OAK-4001, a provider content policy block (n = 467).
- 23.3% of failures were INTERNAL_SERVER_ERROR (n = 467).
- 4.1% of all video jobs ended in a content or copyright block (n = 4,069).
Other codes showed up too: OAK-6002, OAK-4004, OAK-9001, OAK-2001 and UNKNOWN_ERROR. Each had fewer than 100 failures, so we do not publish a share for them. A share built on a few dozen jobs moves too much from week to week to be useful.
What do the OAK error codes mean in plain words?
Oakgen tags every failure with a code. Here is what each one you are likely to see means.
| Code | Plain meaning | Retry as is? |
|---|---|---|
| OAK-4001 | The model provider refused the request under its content policy. | No. Change the prompt or image. |
| OAK-4002 | The provider's safety checker rejected the input or the output. | No. Change the prompt or image. |
| OAK-4004 | The provider flagged the input or output as possible copyrighted material. | No. Remove the protected element. |
| INTERNAL_SERVER_ERROR | Something broke on a server. It says nothing about your prompt. | Yes, once. |
| OAK-6002 | The provider reported a failure with no known cause. | Yes, once. |
| OAK-2001 | The provider rejected Oakgen's credentials. This is on our side. | Wait and retry later. |
| OAK-9001 | The error could not be classified. | Try once more, then contact support. |
The meanings come from Oakgen's error codebook, which every generation job uses.
How do you avoid content filter blocks?
Filter blocks were the largest single group of failures, so they are the best place to save time. These habits cut most of them.
- Describe, do not name. A named celebrity, a brand mascot or a film character is the fastest way to an OAK-4001 or OAK-4004. Describe the look instead ("a woman in her 30s with short red hair").
- Use photos you own. A screenshot from a film, a logo or a famous photo can trip the copyright check. Upload your own image.
- Keep it clothed and calm. Prompts that hint at nudity, injury or weapons trip safety checks even when the intent is harmless. Reword before you retry.
- Change one thing at a time. If a clip is blocked, edit the prompt or swap the image, not both. Then you learn which one tripped the filter.
- Switch models when a prompt is fine. Each provider runs its own filter. A plain prompt blocked on one model can pass on another.
For trend videos the picture is different, because the scene is fixed and only your photo changes. We cover that in why AI video trends get blocked.
When should you retry a failed AI video?
Use the code to decide.
- Retry once on INTERNAL_SERVER_ERROR or OAK-6002.
- Never retry OAK-4001, OAK-4002 or OAK-4004 without changing the input.
- Wait a few minutes on OAK-2001. It is not your fault.
A blind retry costs time. Our guide to the cost of a finished AI video clip shows why the median clip is worth getting right the first time. For trends, see the AI trend video retry budget.
Pick a model that fits the prompt
Run the same idea on Kling, Seedance, Grok or MiniMax from one workspace and see which one accepts it.
How does this compare with other platforms?
We could not find another platform that publishes its video failure rate with a sample size. Providers publish volume, not failures. Google said Flow users generated more than 275 million videos in five months (Google, October 15, 2025). Kuaishou said Kling had made more than 600 million videos by December 2025 (Kuaishou Technology, January 13, 2026). Neither says how many failed.
That is the gap this index fills. It is one platform's number, not an industry rate. Read it as a floor for what to expect, not a promise.
How we measured this
- Dataset. The Oakgen AI Video Index 2026 covers every video job on Oakgen from January 10 to November 10, 2026 (n = 4,069).
- Status. A job counts as failed if its final status was failed. Jobs still processing were left out of both counts.
- Error codes. Failures were grouped by the error type stored on the job. The content filter group adds OAK-4001, OAK-4002, OAK-4004 and the provider CONTENT_POLICY type.
- Privacy. We used aggregate counts only. No prompts, images or user-level data appear in this post.
- Suppression. Any cut with fewer than 100 jobs is suppressed and not published.
What are the limits of this data?
- Single platform. These are Oakgen jobs. Other tools use other filters.
- Small sample. 4,069 jobs and 467 failures is enough for the headline numbers, not for every code.
- Uneven months. Volume rose sharply in October and November 2026, so recent behavior weighs more.
- Filters change. Providers update their rules without notice. A prompt blocked today may pass next month, or the other way round.
The full table, including cuts we suppressed and why, is on the AI video statistics hub. For background on how retries and refunds work across providers, read why AI generations fail.
Frequently asked questions
What is the most common reason an AI video fails?
Content and copyright filters. 35.8% of the 467 failed video jobs were blocked by a content or copyright filter (OAK-4001, OAK-4002, OAK-4004 or a provider content policy error). The single largest code was OAK-4001, the provider content policy block, at 24.4% of failures.
What does OAK-4001 mean?
OAK-4001 means the model provider refused the request on content policy grounds. The prompt, the uploaded image or the output tripped the provider's rules. Running the same request again will usually fail the same way.
Should I retry a failed AI video?
Retry server errors (INTERNAL_SERVER_ERROR, OAK-6002) once. Do not retry filter blocks (OAK-4001, OAK-4002, OAK-4004) unchanged. Change the prompt or the input image first.
Is this data from all AI video tools?
No. It covers video jobs on Oakgen only. Other platforms use different models, filters and retry logic, so their failure rates will differ.
