If your budget for AI video sits below $0.40 per clip, the real choice in 2026 is between Hailuo 2.3 and Wan 2.5. Hailuo gives you faster iteration and noticeably more motion variety out of the box. Wan gives you a cheaper hosted clip, and its 2.2 release gives you a self-hostable option Hailuo has no answer to. We ran both on the same prompt set from the 8frame canvas to see exactly where each one wins and where each one falls short on a "hailuo vs wan ai video" test.
TL;DR
- Hailuo 2.3 is faster (~50s per 5s clip), sharper on motion variety, best for social b-roll and quick UGC iterations
- Wan 2.2 is cheaper (50 credits a clip on 8frame vs 88 for Hailuo) and self-hostable under Apache 2.0; Wan 2.5 is 102 and API-only
- Neither beats Kling on quality per dollar once you're billing a client; Wan undercuts it on raw cost per clip
- For genuinely free output, self-hosted Wan 2.2 on your own GPU is the answer; Wan 2.5 has no public weights
The budget test prompt
We picked a prompt that stresses the two things budget models get wrong most often: natural motion and accurate lighting.
A barista pours steamed milk into a ceramic coffee cup in slow motion. Top-down angle, warm café light, soft focus background, 5-second clip, 1080p.
We ran it through both models at their default settings on the 8frame canvas in late May 2026, locking resolution to 1080p for a fair comparison. We measured generation time, motion smoothness, lighting fidelity, and cost per clip.
Hailuo 2.3: what we observed
Prompt: "A barista pours steamed milk into a ceramic coffee cup in slow motion. Top-down angle, warm café light, soft focus background, 5-second clip." The milk pour motion was fluid and physically plausible. The slow-motion interpretation held up for the full five seconds without the frame-rate artifacts you see in weaker models. Background blur was applied correctly. Warm tones were present but ran slightly orange rather than true golden-hour. Generation time was 48 seconds.
Prompt: "Street food vendor tosses noodles in a wok over an open flame. Side angle, night market lighting, 5-second clip." Strong motion here. The flame had real flicker behavior and the noodle toss followed a plausible arc. The vendor's hands were slightly smeared at the peak of the toss, which is a known Hailuo weakness on fast hand motion. Night market atmosphere was convincing, with light spill from adjacent stalls visible in the background.
Prompt: "Close-up of rain falling on a forest path. Shallow depth of field, overcast diffused light, 5-second clip." This is where Hailuo's motion variety shows best. Individual rain drops were distinct in the foreground and blurred correctly into the bokeh zone. The path surface showed realistic ripple effects. Generation took 52 seconds, slightly above average for this model.
Prompt: "Aerial drone shot pulling back from a rooftop garden. Golden hour, urban skyline in background, 5-second clip." The drone motion path felt synthetic at the midpoint, with a slight stutter as the camera reached the edge of the generated frame. Skyline detail held up well. This is a prompt where Kling 3.0 would perform noticeably better, but at roughly half the price Hailuo's output was usable for b-roll.
Wan 2.5: what we observed
Prompt: "A barista pours steamed milk into a ceramic coffee cup in slow motion. Top-down angle, warm café light, soft focus background, 5-second clip." The motion was correct but softer than Hailuo's output. The slow-motion effect was achieved more through reduced frame velocity than through true slow-motion rendering, which becomes visible when you play the clip at full speed. Warm lighting was present and better tuned to an indoor café color temperature than Hailuo's output. Generation took 43 seconds.
Prompt: "Street food vendor tosses noodles in a wok over an open flame. Side angle, night market lighting, 5-second clip." Wan handled the flame reasonably well at this price point. The noodle motion was less detailed than Hailuo's output and the hands were cleaner, suggesting Wan prioritizes edge-sharpness on subjects over motion fidelity in fast-action sequences. The night market atmosphere was flatter, with less convincing light spill from surrounding stalls.
Prompt: "Close-up of rain falling on a forest path. Shallow depth of field, overcast diffused light, 5-second clip." Softer overall. Rain drops merged in the midground rather than staying distinct through the depth range, which is the inverse of Hailuo's result on the same prompt. The path color temperature was accurate. Usable for social if you're not playing it on a large screen.
Prompt: "Timelapse of clouds moving over a mountain ridge. Wide angle, dusk light, 5-second clip." This is where Wan surprised us. Cloud motion was smoother and more naturalistic than Hailuo on this specific prompt type. The dusk color gradient from orange to deep blue was well rendered. For slow-moving natural phenomena like clouds, ocean waves, or fog, Wan 2.5 is competitive with models that cost twice as much.
Strengths
Hailuo 2.3 wins on motion variety. Fast-action prompts, close-up textures with real movement (pouring liquids, fire, foliage), and multi-element scenes where several things are moving at once all produce better results than Wan at equivalent settings. The model also renders more reliably at consistent quality across diverse prompt types. If you're generating 20 different clips across 20 different subjects, Hailuo's output variance is lower.
Wan wins on flexibility and cost. Wan 2.2 runs locally on a machine with 24GB VRAM, which matters for studios with volume requirements and data-privacy constraints. On 8frame Wan 2.2 runs 50 credits a clip against Hailuo's 88, and the local option means a studio that owns the hardware pays nothing per clip, which makes large-batch b-roll production viable in a way the other models don't. For slow atmospheric content, natural phenomena, and wide establishing shots, it's competitive well above its price point.
Weaknesses
Hailuo 2.3 degrades on fast hand and finger motion. Detailed human interaction with objects (typing, crafting, surgical close-ups) produces smeared or blended extremities. It's also slower than Wan on simple, low-motion prompts where the extra motion fidelity isn't needed, meaning you're sometimes paying the time cost for capability you're not using.
Wan 2.5 loses detail in the midground of complex scenes. In multi-depth prompts where the camera sees near, mid, and far subjects simultaneously, Wan tends to sharpen the foreground and flatten everything behind it. This is fine for social content viewed at phone scale and a problem for anything delivered at 1080p full-screen. The model also requires more prompt specificity to get consistent results; vague prompts produce more variation than on Hailuo.
Best by use case
B-roll for social content: Wan 2.2. The output quality matches what you need for Instagram Reels or TikTok backgrounds, and at 50 credits a clip you can batch 10 clips in a single session for 500 credits, well inside one $19 Starter month.
UGC ads with motion-heavy subjects: Hailuo 2.3. The motion fidelity gap matters when you're showing a product being used, a person reacting, or anything where the clip's job is to feel kinetic. Hailuo gives you that at roughly $0.30 per clip, which is still below every alternative except Wan.
High-volume b-roll production (50+ clips): Wan 2.2. At 50 credits a clip, a 50-clip batch runs 2,500 credits (about $25 in never-expiring top-up packs), and if you self-host its Apache 2.0 weights it's free. That's the right answer for library building, background texture packs, and content pipelines where individual clip quality matters less than per-clip cost.
Slow atmospheric content (clouds, water, fog, fire): Wan 2.5. It handles these better than its price suggests, and these prompt types are exactly where it closes the quality gap with Hailuo.
Local or private pipeline: Wan 2.2, the last Wan with published weights. Hailuo has no local option. If your use case requires the model to run on your own hardware, Wan is the only choice in this price tier.
Pricing math
Here's what each model costs per 5-second clip on the 8frame canvas today, in credits. A credit is about a cent at the $10-per-1,000 top-up pack rate.
| Model | Credits per 5s clip | Native resolution | Avg generation time |
|---|---|---|---|
| Hailuo (H3) | 88 | 1080p / 30fps | ~50s |
| Wan 2.5 (hosted) | 65 | 720p to 1080p / 24fps | ~45s |
| Wan 2.2 (self-hosted) | 0 (Apache 2.0, your GPU) | 720p / 24fps | hardware-dependent |
For comparison, Kling v3 Standard runs 86 credits at native 4K. The Hailuo price delta against Kling is small enough that if quality matters for a specific clip, Kling is usually the better call. The Wan delta against both is large enough to make it the default when cost is the constraint.
One 8frame credit pool covers all of these models, so if you're already on 8frame you're not managing separate accounts or API keys to switch between them.
FAQ
Is Hailuo 2.3 better than Wan 2.5 for AI video?
It depends on what "better" means for your job. Hailuo 2.3 produces more consistent motion and handles fast-action prompts more reliably. Wan costs significantly less, runs locally in its 2.2 release, and handles slow atmospheric content comparably. For paid client work with motion-heavy requirements, Hailuo. For high-volume b-roll on a tight budget, Wan.
Can I use Wan 2.5 for free?
Only by self-hosting Wan 2.2, whose weights are published, so a machine with a 24GB-class GPU runs it with no per-clip cost, watermark-free. Wan 2.5 has no public weights. On 8frame there's no free tier: Wan 2.5 runs 102 credits a clip and Wan 2.2 runs 50, about 9 or 20 clips on the $19/month Starter plan. Hailuo has no open weights either, so hosted is the only way to run it at all.
Which budget AI video model is best for social media content?
For short-form social where you need fast iteration and decent motion (UGC ads, product demos, Reels), Hailuo 2.3 is the better pick. For background b-roll, slow footage, or anything where you're producing a lot of clips and cost per clip matters more than per-clip perfection, Wan 2.5 is the right answer. The honest take: run both on your specific prompt type before committing to a workflow. They're cheap enough that the test costs about 150 credits, a dollar and a half at pack rate.
The best AI video generator comparison for 2026 covers the full 16-model field if you want to see where Hailuo and Wan sit against the premium tier. If you're using Wan 2.5 for b-roll production, Wan 2.5 prompts for free b-roll has the prompt formulas that consistently produce usable footage on the first try.
Ready to run this comparison yourself? The 8frame multi-model workflow lets you submit the same prompt to both models side by side and compare output for about 150 credits.