Best GPU for LTX-Video in 2026: 5 Picks (Real-Time)

From the Best GPU for AI archive. The canonical version has interactive calculators, an up-to-date GPU comparison table, and live pricing.

LTX-Video is the first open-source video model that genuinely feels interactive. Lightricks shipped it late 2025, and by May 2026 it has become the go-to local pick for creators who want to iterate on prompts without waiting 20 minutes for each clip. On a 4090, a 5-second 768x512 generation finishes before the clip would even finish playing — that is the hook, and it is real.

Quick answer: The RTX 4090 (24GB) is the best GPU for LTX-Video in 2026. It generates faster than real time on standard clips, has the VRAM for longer durations and i2v with reference images, and prices have settled at ~$1,600. The RTX 5090 is faster but pricier; a 16GB card like the RTX 5070 Ti is the budget floor.

See the recommended pick on the original guide

Who this is for

This guide is for people generating short AI video locally with LTX-Video — social creators iterating on hooks, indie animators prototyping shots, and developers building on top of the model. If you batch-render long Sora-style cinematics overnight, this is not your guide. LTX-Video earns its keep when you want to try ten variations of a prompt in the next ten minutes.

What LTX-Video actually needs

LTX-Video is unusually efficient for a video model. The 2B-parameter DiT architecture and Lightricks' aggressive optimization mean it fits where Hunyuan and CogVideoX-5B do not. Realistic VRAM at common settings:

In practice 12GB cards run the model but you fight constant memory pressure. 16GB is the comfortable floor. 24GB is where the workflow opens up — multiple LoRAs, longer durations, queued generations.

LTX-Video generation speed ranked

These are wall-clock seconds for a single 5-second 768x512 clip at default settings (30 steps, fp8). Numbers come from our own ComfyUI runs and community benchmarks; expect ±10% variance depending on your sampler and node graph.

A 5-second clip plays for 5 seconds. The 4090 and 5090 generate it faster than that — that is what Lightricks means by "faster than real time." Everything from the 5080 down is still fast enough to iterate, just not literally instantaneous.

See the recommended pick on the original guide

RTX 4090 — the right answer for most people

The 4090 is the GPU LTX-Video was tuned around in the community. 24GB of GDDR6X means you stop thinking about memory and start thinking about prompts. In our experience, the 4090's 24GB lets you stage 3-4 generations in queue while the next one renders, run a refiner pass, and keep ComfyUI's preview pipeline live without OOMs. That workflow alone is worth the price gap over 16GB cards.

The other quiet win: i2v (image-to-video) with a high-resolution reference frame fits comfortably. On 16GB you have to downscale references or trim frame counts. On 24GB you do not.

RTX 5090 — only if you batch

The 5090 generates roughly 25-30% faster than the 4090 and gives you 32GB. For interactive single-shot work that gap barely matters — both finish before you can read the seed. Where the 5090 pays back is batch: queue up 50 prompts overnight and it will finish meaningfully sooner. If you are not batching, the $400 premium over a 4090 buys you bragging rights more than throughput.

See the recommended pick on the original guide

Mid-range: RTX 5080 and 5070 Ti

Both are 16GB, both run LTX-Video well at standard settings. The 5080 is roughly 30% faster than the 5070 Ti and worth the gap if you can stretch the budget. The 5070 Ti at ~$750 is the value sweet spot in the mid-range — fast enough to feel interactive, with enough VRAM to handle i2v and standard clip lengths.

What you give up at 16GB: long clips at higher resolution start hitting memory ceilings, and you cannot stack ControlNet + multiple LoRAs the way 24GB cards can.

See the recommended pick on the original guide

Budget pick: RTX 4060 Ti 16GB

At ~$400 the 4060 Ti 16GB is the cheapest card we recommend for LTX-Video. It is meaningfully slower than the 5070 Ti — about 2x — but 16 seconds per clip is still usable. If you are learning the tool, prototyping concepts before committing to longer renders, or your video gen is a side project rather than a full workflow, this card does the job.

See the recommended pick on the original guide

Used RTX 3090 — the wildcard

A used 3090 at ~$700 gives you 24GB of VRAM for less than half what a 4090 costs. LTX-Video runs noticeably slower than on the 4090 (the memory bandwidth difference shows) but you get the same VRAM ceiling. If you are price-sensitive but want 24GB for longer clips and reference frames, a tested used 3090 is a defensible pick. Just buy from a seller with returns.

Should you just use cloud?

Image-to-video at scale often pencils out better on cloud than on your own hardware. RunPod's A6000 and L40S instances run LTX-Video at full quality, and if you are spinning up generation jobs 3-4 hours a week the rental cost stays under what GPU depreciation alone would be. For experimentation, learning the model, or one-off campaigns, cloud is the honest answer.

Where local wins: daily iteration, working without an internet dependency, and the privacy of keeping reference imagery off third-party servers.

Which GPU should YOU buy?

• Real-time interactive work — your main creative tool? RTX 4090 (24GB). Faster-than-real-time generation, headroom for i2v with reference frames, room for LoRA stacks.
• Batch generation, dozens of clips per session? RTX 5090 (32GB). The 25-30% speed advantage and extra VRAM matter when you are queueing 50+ jobs.
• Hobbyist, learning the model, occasional clips? RTX 4060 Ti 16GB (~$400) or used RTX 3090 (~$700). Both are honest entry points.
• Mid-range new build? RTX 5070 Ti (16GB) at $750 is the value sweet spot — fast enough to feel interactive without flagship pricing.
• Generate fewer than 5-10 clips a week? Skip the hardware entirely. RunPod is cheaper than a depreciation curve.

Common mistakes to avoid

• Expecting Sora-quality output. LTX-Video is not Sora. Set expectations — it produces good 5-10 second clips with sometimes-shaky temporal coherence, not 60-second cinematic perfection. The trade-off for speed is fidelity, and that trade-off is the point of the model.
• Underestimating temporal coherence at low VRAM. Pushing duration on a 12GB card forces the sampler into corners and you get more flicker, more identity drift on subjects, more "morph" artifacts. If coherence matters, do not undershoot VRAM.
• Running fp16 when fp8 will do. The fp8 build is roughly 2x faster with quality differences most viewers cannot see at 768x512. Default to fp8 unless you have a specific reason not to.
• Buying a 4090 for occasional use. If you generate 10 clips a month, you have just bought a $1,600 ornament. Use RunPod and put the money elsewhere.

Final verdict

See the recommended pick on the original guide

LTX-Video changes the local AI video math. It is the first open model where "buy a 4090 and iterate fast" beats "rent an H100 and wait." For broader video-gen context see our best GPU for AI video overview, our AI animation GPU picks for AnimateDiff and SVD workflows, or the Hunyuan-Video hardware breakdown if you want the higher-fidelity (and much slower) alternative. Browse our full Guides library for related video-gen comparisons.

LTX-Video is not Sora — and that is the feature, not the bug. Buy the 4090, iterate ten times in the time Hunyuan renders once.

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Read the full guide on Best GPU for AI — includes our VRAM calculator, GPU comparison table, and live pricing.