첫 번째 항목은 항상 핀의 출처입니다. 전체 신뢰도는 각 자료가 위의 시작·종료 시각을 얼마나 확실히 뒷받침하는지에 대한 가중 평균이며, 자료는 최신 자료보다 180일 오래될 때마다 가중치가 절반이 됩니다.
Estimated: the press release is datelined Beijing, 24 September 2025 ("today announced"), ScriptByAI[4] gives 23 September and Kling's 2 October release says the model was "released less than a week ago".
9 October 2025 hands-on: a 'very impressive tool', strong text-to-video and image-to-video, but it would not perform a requested somersault and added unrequested breathing sound.[1]
2 October 2025 Kling release: tops both Artificial Analysis video arenas ahead of Veo 3 and Luma Ray 3; 5 and 10 second clips up to 1080p at 25 credits per 5 seconds.[1]
Dates Kling 2.5 Turbo to 23 September 2025 and cuts the 1080p five-second price from 35 to 25 credits.[1]
빠지거나 잘못된 점이 있나요? 이 핀을 뒷받침하는 링크, 다른 시작일이나 종료일과 그 이유, 빠지거나 잘못된 사실을 자신의 말로 알려주세요. AI가 이 핀의 출처와 대조하고 더 나은 자료를 찾아, 뒷받침하는 페이지를 추가합니다. 핀 자체의 출처가 여전히 가장 중요하게 반영됩니다. AI는 이미지도 확인합니다. 다른 것을 보여주거나 제대로 보여주지 못하는 이미지는 뒤로 옮기거나 교체합니다.
| 2.5 Turbo Pro, 5 s |
|---|
| $0.35 (USD) |
| Each additional second | $0.07 (USD) |
|---|
Price as listed on the fal.ai endpoint page, read 24 Oct 2026; same figures on the image-to-video endpoint. · 출처
| Comparison | Win-loss ratio |
|---|---|
| Text-to-video vs Seedance 1.0 mini | 285% |
| Text-to-video vs Veo3-fast | 212% |
| Text-to-video vs Seedance 1.0 | 160% |
| Image-to-video vs Seedance 1.0 mini | 208% |
| Image-to-video vs Veo3-fast | 289% |
| Image-to-video vs Seedance 1.0 | 164% |
Kling's internal test with invited professionals voting on pairs; not independent. Kling also reports 2.5 Turbo ranked No.1 in Artificial Analysis's text-to-video and image-to-video arenas on 2 Oct 2025 (no Elo figure given). · 출처
I will admit that it’s a very impressive tool as of right now.
Kling's 2.5 / 3.0 line has excellent motion coherence — weight, momentum and object interactions tend to hold together where Veo occasionally softens.
Kling AI’s 2.5 Turbo Video model outperformed Google’s Veo 3 and Luma Labs’ Ray 3 to secure the No.1 spot in both the text-to-video and image-to-video leaderboards
