How to Compare AI Video Models: Method, Cost and Sora Archives

Revised October 19, 2026. This guide originally compared Sora, Veo and Pika. Sora generation is now closed on MaxVideoAI. The old price table and unsupported quality and speed claims have been removed. Use the method below for models currently available in the workspace.

A useful comparison starts with a shot you need to deliver. An attractive demo, an editorial score and a measured production time answer different questions; none guarantees that your next generation will work.

What changed in the original comparison?

The Sora 2 archive documents past capabilities and examples. It is not an option for new generations. OpenAI’s discontinuation notice gives the announced API closure date of September 24, 2026.

Veo and Pika are model families: a comparison must name the exact version and supported mode. The original article did not publish a controlled test set for its claims about realism, speed or price. Those claims should not be treated as benchmark results. It also referred to Dolby Vision previews and automatic render-log exports without sufficient supporting evidence; those promises have been removed.

For a new project, start from the current model catalog. Check availability, supported inputs and controls on the model page before choosing two candidates. A historical model page does not establish current availability.

1. Define the same deliverable

Write down the shot, target duration, resolution, aspect ratio, audio requirement and reference assets. Compare settings both models actually support. If you cannot match a setting, record the difference next to the result.

For example: a single product shot with a slow camera movement and a readable label. Decide beforehand whether label accuracy, camera motion or subject consistency matters most. This is a suggested test brief, not a claim that MaxVideoAI has run it on every model.

2. Compare the quoted cost

Use the pricing page and the quote shown before generation. Record the model version, mode, duration, resolution, audio options and quoted total. Two prices for different resolutions or modes are not an equivalent comparison.

Do not reuse the former eight-second price table: it lacked a reproducible configuration and is no longer a reliable purchasing guide. Include paid retries when estimating the cost of a usable clip. A low price per attempt does not establish a lower cost per finished shot.

3. Keep the inputs and record the results

Use the same prompt and reference assets where supported. Record any prompt adaptation needed by a model. Save the settings, date, job reference and output for each attempt. Keep unsuccessful attempts in your notes as well as the selected result.

A single clip can reveal a problem, but it cannot establish a stable ranking. If you make several attempts, state how many you made and how you chose the published result. Do not describe independent showcase clips made with different prompts as a controlled comparison.

4. Separate capability, judgment and timing

• Capability: check the model page and linked provider documentation for supported inputs, output formats and limits.
• Visual judgment: evaluate prompt adherence, motion, identity, readable text and audio against your brief. Explain the visible failure or strength.
• Timing: record the interval you measured. Provider execution, the time until a clip appears in your workspace, and a later file update are different events.

Benchmark Lab explains MaxVideoAI’s editorial scorecards and production timing methodology. Editorial scores are judgments, not a substitute for documented runs under matched conditions. Production traffic also mixes settings and queue conditions.

5. Choose for the next shot

Choose the model that satisfies your required inputs and produces an acceptable result at the quoted cost. Keep the evidence for that decision rather than declaring a universal winner for realism, style or speed.

For a worked production example, read how we made an AI podcast with Codex and MaxVideoAI. It includes the workflow, revisions and editing choices. The Wan 3 Prime match-cut example shows a published output and prompt; it is a demonstration, not a cross-model benchmark.

Common questions

Can I still generate with Sora on MaxVideoAI?

No. New Sora generations are closed. Existing archive pages describe historical work. Choose an available model explicitly for a new job.

Which model is cheapest or fastest?

That depends on the configuration and current conditions. Compare current quotes for the same deliverable, then use documented attempts and the timing methodology to assess the trade-off.

Can I compare the same prompt across models?

Yes, when their input requirements support it. Preserve the prompt and assets, record any changes, and select each model and its settings explicitly before approving a new generation.

MaxVideoAI sells access to the models it covers. The editorial standards explain how sourced facts and editorial judgments are distinguished.