{"id":2074,"date":"2026-05-04T09:00:00","date_gmt":"2026-05-04T09:00:00","guid":{"rendered":"https:\/\/wiro.ai\/blog\/?p=2074"},"modified":"2026-09-27T17:57:30","modified_gmt":"2026-09-27T17:57:30","slug":"top-5-image-to-video-apis-in-2026-1-base-image-test","status":"publish","type":"post","link":"https:\/\/wiro.ai\/blog\/top-5-image-to-video-apis-in-2026-1-base-image-test\/","title":{"rendered":"Top 5 Image-to-Video APIs in 2026: 1 Base Image Test"},"content":{"rendered":"<h2>One first frame, five different motion systems<\/h2>\n<p>Image-to-video comparisons are only useful when the starting conditions stay fixed. This test used one still image of a white paper airplane on a sunlit wooden desk, then asked every model for the same basic event: lift gently, glide forward, keep the office believable, and let the camera track slowly. That is deliberately not a fireworks prompt. It is a continuity test. The paper edges, desk grain, window lines, chair geometry and light shafts make it easier to see whether a model can add motion without quietly rebuilding the scene.<\/p>\n<h2>Base image used for every run<\/h2>\n<figure>\n  <img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"1024\" class=\"wp-image-2066\" src=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base.png\" alt=\"A white paper airplane resting on a wooden desk in a bright modern office\" srcset=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base.png 1024w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-510x510.webp 510w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-900x900.webp 900w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-150x150.webp 150w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-768x768.webp 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption>Prompt used to make the starting frame: Realistic photo. A white paper airplane resting on a wooden desk in a bright modern open plan office. Morning sunlight through large windows. Shallow depth of field. Crisp details. Natural colors.<\/figcaption><\/figure>\n<h2>Test setup and what is being measured<\/h2>\n<p>The shared motion prompt was: <em>Animate the scene realistically. The paper airplane gently lifts off the desk and glides forward. Slow tracking camera move. Subtle dust particles in sun rays. Natural motion. Keep the office consistent.<\/em> The scorecard is qualitative rather than synthetic: first-frame fidelity, whether the airplane remains a coherent folded object, whether the desk and windows stay stable, how well the requested camera move reads, and whether the generated clip is useful without a repair pass. These are single outputs, not a claim that one result predicts every prompt or seed.<\/p>\n<p>Each test kept the short-duration setting used in the original run: five seconds for PixVerse V5, Seedance Lite, Kling v2.1 Master and PixVerse Transition; six seconds for Hailuo-02. The recorded wall-clock times below are the original Wiro task times, so they include the service-side queue and processing experienced by that run rather than a benchmark of raw inference. The model documentation available for these listings describes inputs and options, but does not expose a per-output Wiro price for these exact historical configurations. Rather than reverse-engineer a cost from an unrelated example, this article leaves cost as not disclosed for each result.<\/p>\n<h2>Models tested<\/h2>\n<ul>\n<li><a href=\"https:\/\/wiro.ai\/models\/pixverse\/image-to-video-v5\">PixVerse Image-to-Video v5<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/bytedance\/image-to-video-seedance-lite-v1\">ByteDance Seedance Lite v1 (Image-to-Video)<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/klingai\/image-to-video-klingai-v2-1-master\">KlingAI v2.1 Master (Image-to-Video)<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/minimax\/image-to-video-hailuo-02\">MiniMax Hailuo-02 (Image-to-Video)<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/pixverse\/transition\">PixVerse Transition (v5)<\/a><\/li>\n<\/ul>\n<h2>What each output shows<\/h2>\n<h3>PixVerse Image-to-Video v5: flexible output controls for a one-frame clip<\/h3>\n<p><video controls preload=\"metadata\" src=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-pixverse-v5.mp4\"><\/video><\/p>\n<p>This clip asks PixVerse V5 to turn a static product-like image into a restrained movement shot. The useful inspection points are the paper folds and the near-field desk texture: both are small, high-contrast details that can break when a generator tries to create forward travel. PixVerse exposes duration choices of 5 or 8 seconds, 360p through 1080p quality options, an optional style, a seed, a negative prompt and a watermark toggle. This run was 5 seconds; the original post did not record the selected quality, style, seed or negative prompt, so it would be misleading to fill them in after the fact. Recorded elapsed time: 86 seconds. Wiro cost for this configuration: not disclosed in the documentation.<\/p>\n<p>Pick PixVerse V5 when you want explicit resolution and duration choices around a conventional single-image animation, especially when you also need a negative prompt or a stylized treatment. The trade-off is that more exposed controls also mean more decisions to standardize when comparing batches. <a href=\"https:\/\/pixverse.ai\/en\" target=\"_blank\" rel=\"noopener\">PixVerse\u2019s official site<\/a> is a useful primary reference for its current product direction.<\/p>\n<h3>ByteDance Seedance Lite v1: the quickest result in this run<\/h3>\n<p><video controls preload=\"metadata\" src=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-seedance-lite.mp4\"><\/video><\/p>\n<p>The Seedance Lite result keeps the composition close to the source image and makes the requested movement modest. That restraint is valuable here: the scene has no reason to acquire a dramatic camera move or redesigned office furniture. Its Wiro model page supports a first image and optional final image, 5- or 10-second duration, 480p, 720p or 1080p resolution, aspect-ratio controls at lower resolutions, watermark, seed and a fixed-camera option. This original run was 5 seconds and completed in 31 seconds, the shortest recorded time of the set. The saved post does not preserve its resolution, seed, ratio or camera-fixed selection; cost is likewise not disclosed for the exact run.<\/p>\n<p>Choose Seedance Lite when turnaround and conservative source-image adherence matter more than showing off large camera choreography. Its optional last frame also makes it worth testing for shots where an editor already knows the intended destination frame.<\/p>\n<h3>KlingAI v2.1 Master: stronger movement, longest wait<\/h3>\n<p><video controls preload=\"metadata\" src=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-kling-v2-1-master.mp4\"><\/video><\/p>\n<p>Kling\u2019s output is the one to scrutinize for environmental drift. A slow tracking instruction can create convincing depth, but it can also cause window frames, chair edges and background detail to be regenerated rather than carried forward. The docs specify 5- and 10-second clips at 720p and 30 fps, with a first-frame image, prompt, negative prompt and CFG scale. This was a 5-second clip; the original record does not state its scale or negative prompt. It took 558 seconds, far longer than the other samples, and no exact Wiro cost is exposed for the historical run.<\/p>\n<p>Pick Kling v2.1 Master when you are prepared to spend more time reviewing a shot whose camera language matters. It is the least attractive choice in this small sample when fast iteration is the deciding factor. For current maker context, see the <a href=\"https:\/\/kling.ai\/\" target=\"_blank\" rel=\"noopener\">official Kling site<\/a>; product pages change faster than a frozen comparison does.<\/p>\n<h3>MiniMax Hailuo-02: short, smooth six-second option<\/h3>\n<p><video controls preload=\"metadata\" src=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-hailuo-02.mp4\"><\/video><\/p>\n<p>Hailuo-02\u2019s result is best read as a short continuity test: does the airplane still look folded as it moves, and do the light shafts remain part of the same room? The available controls are a first image, optional last image, prompt optimizer, 768P or 1080P resolution, and 6- or 10-second duration. The documentation notes that 1080P is limited to six seconds, while ten seconds is available at 768P. This saved output is 6 seconds and took 91 seconds. Its exact resolution and prompt-optimizer state were not retained in the source post, so they are not asserted here; Wiro cost is not disclosed for this run.<\/p>\n<p>Choose Hailuo-02 when a six-second clip is enough and you want a model with an optional end-frame path. It is a pragmatic middle option in this test: materially quicker than Kling, longer than the five-second samples, and not a substitute for a dedicated transition model when the final composition must be exact. <a href=\"https:\/\/hailuoai.video\/\" target=\"_blank\" rel=\"noopener\">Hailuo\u2019s official site<\/a> provides the maker\u2019s current product information.<\/p>\n<h3>PixVerse Transition v5: a different test because it has a destination frame<\/h3>\n<p>Transition is not directly equivalent to the four one-frame runs. It takes a first and a second image, which changes the problem from \u201cinvent a plausible next few seconds\u201d to \u201cconnect these two compositions.\u201d For fairness, the second frame preserved the same office and airplane but placed the aircraft slightly above the desk.<\/p>\n<figure>\n  <img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"1024\" class=\"wp-image-2067\" src=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-2.png\" alt=\"A white paper airplane flying slightly above a desk in the same bright office\" srcset=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-2.png 1024w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-2-510x510.webp 510w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-2-900x900.webp 900w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-2-150x150.webp 150w, https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-base-2-768x768.webp 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption>End-frame prompt: Realistic photo. A white paper airplane flying slightly above a wooden desk in a bright modern open plan office. Morning sunlight through large windows. Shallow depth of field. Crisp details. Natural colors.<\/figcaption><\/figure>\n<p><video controls preload=\"metadata\" src=\"https:\/\/wiro.ai\/blog\/wp-content\/uploads\/2026\/03\/i2v-roundup-pixverse-transition-v5.mp4\"><\/video><\/p>\n<p>The output is useful precisely because it has a visual target. Rather than hoping the plane ends in the right place, the run can interpolate toward an approved frame. PixVerse Transition offers v3.5, v4, v4.5 and v5 model selections; 5- or 8-second duration; 360p through 1080p quality; normal or fast motion where supported; and a seed. The original result used v5 for 5 seconds and recorded 108 seconds. The quality, seed and exact motion setting were not retained; no exact Wiro cost is published in the supplied documentation.<\/p>\n<p>Use Transition when the beginning and ending visual states are already designed: a product reveal, controlled outfit change, or edit-point bridge. Use a one-frame model instead when the task is to discover motion from a single keyframe.<\/p>\n<h2>Comparison table<\/h2>\n<table>\n<thead>\n<tr>\n<th>Model<\/th>\n<th>Frame inputs<\/th>\n<th>Saved duration<\/th>\n<th>Recorded run time<\/th>\n<th>Cost shown in docs\/run<\/th>\n<th>Best fit<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>PixVerse V5<\/td>\n<td>First frame<\/td>\n<td>5s<\/td>\n<td>86s<\/td>\n<td>Not disclosed<\/td>\n<td>Configurable single-image motion<\/td>\n<\/tr>\n<tr>\n<td>Seedance Lite v1<\/td>\n<td>First frame; optional last frame<\/td>\n<td>5s<\/td>\n<td>31s<\/td>\n<td>Not disclosed<\/td>\n<td>Quick, restrained iterations<\/td>\n<\/tr>\n<tr>\n<td>Kling v2.1 Master<\/td>\n<td>First frame<\/td>\n<td>5s<\/td>\n<td>558s<\/td>\n<td>Not disclosed<\/td>\n<td>Shots where camera ambition merits review time<\/td>\n<\/tr>\n<tr>\n<td>Hailuo-02<\/td>\n<td>First frame; optional last frame<\/td>\n<td>6s<\/td>\n<td>91s<\/td>\n<td>Not disclosed<\/td>\n<td>Short smooth clips and end-frame experiments<\/td>\n<\/tr>\n<tr>\n<td>PixVerse Transition v5<\/td>\n<td>First and last frame<\/td>\n<td>5s<\/td>\n<td>108s<\/td>\n<td>Not disclosed<\/td>\n<td>Planned A-to-B transitions<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Practical verdict<\/h2>\n<p>There is no universal winner because these tools answer different production questions. Start with Seedance Lite for the fastest pass through a controlled motion brief. Use PixVerse V5 when resolution, style and negative-prompt controls are part of the creative brief. Reserve Kling for sequences where camera movement is worth the much longer recorded turnaround and careful continuity review. Choose Hailuo-02 for its six-second baseline and optional end-frame workflow. Reach for PixVerse Transition only when you can supply both the start and end compositions; that added constraint is its advantage, not a limitation.<\/p>\n<p>For more ways to structure a video-model evaluation, read <a href=\"https:\/\/wiro.ai\/blog\/cinematic-image-to-video-models\/\">our cinematic image-to-video model tests<\/a>, the <a href=\"https:\/\/wiro.ai\/blog\/ltx-2-distilled-8-motion-prompts-for-image-to-video\/\">LTX-2 motion-prompt tests<\/a>, and <a href=\"https:\/\/wiro.ai\/blog\/top-5-text-to-video-apis-in-2026-1-prompt-each\/\">our text-to-video API roundup<\/a>. Keep the base image fixed, name the parameters you actually used, and treat one generation as evidence to inspect\u2014not a leaderboard score.<\/p>\n<h2>Try the models<\/h2>\n<ul>\n<li><a href=\"https:\/\/wiro.ai\/models\/pixverse\/image-to-video-v5\">PixVerse Image-to-Video v5<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/bytedance\/image-to-video-seedance-lite-v1\">ByteDance Seedance Lite v1<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/klingai\/image-to-video-klingai-v2-1-master\">KlingAI v2.1 Master<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/minimax\/image-to-video-hailuo-02\">MiniMax Hailuo-02<\/a><\/li>\n<li><a href=\"https:\/\/wiro.ai\/models\/pixverse\/transition\">PixVerse Transition<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>One first frame, five different motion systems Image-to-video comparisons are only useful when the starting conditions stay fixed. This test used one&hellip;<\/p>\n","protected":false},"author":4,"featured_media":2073,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[53],"tags":[88,117,58,97,118,190,133],"class_list":["post-2074","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-model-roundups","tag-bytedance","tag-hailuo","tag-image-to-video","tag-kling","tag-minimax","tag-pixverse","tag-seedance"],"_links":{"self":[{"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/posts\/2074","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/comments?post=2074"}],"version-history":[{"count":2,"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/posts\/2074\/revisions"}],"predecessor-version":[{"id":4194,"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/posts\/2074\/revisions\/4194"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/media\/2073"}],"wp:attachment":[{"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/media?parent=2074"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/categories?post=2074"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wiro.ai\/blog\/wp-json\/wp\/v2\/tags?post=2074"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}