LTX-Video · 42 cards measured first-party · Updated October 2026
LTX-Video is the accessible end of AI video: a distilled model that generates a 97-frame clip at 704×480, and, unusually for video, runs on as little as ~14GB of VRAM. It's the workload that tells you whether local AI video is realistic on the hardware you already have.
Benchmarked weights: Lightricks/LTX-Video-0.9.5

31.87 frames/s on LTX-Video, the ceiling. Measured on our bench. 288GB of VRAM, $40,000 at launch.
Best for: LTX-Video work where you want the ceiling gone rather than the cheapest entry.

10.45 frames/s on LTX-Video, fastest card you can buy at retail. Measured on our bench. 32GB of VRAM, $1,999 at launch.

1.71 frames/s on LTX-Video, lowest launch price that still fits. Measured on our bench. 16GB of VRAM, $429 at launch.

4.33 frames/s on LTX-Video, most speed per dollar. Measured on our bench. 16GB of VRAM, $999 at launch. That is 4.34 frames/s per $1,000 of launch price.
Compute-bound, but with a system-RAM requirement most benchmarks ignore: the weights need staging, so a card with enough VRAM on a RAM-starved host still fails. We gate on both, which is why some cards you'd expect to see here are absent.
LTX-Video: speed on every GPU we have data for
Top 15 shown; 28 more cards in the full table below.
Single stream, batch size 1. 31 of the 53 cards on this page were measured first-party by us; the rest are anchored estimates against those measurements and are labelled in the table below.
Efficiency: frames/s per 100W drawn
Top 15 shown; 15 more cards in the full table below.
Power is the average pulled during the run, sampled at 1Hz. The fastest card is often not the one here, and for anything left running this is the number that shows up on the bill.
Value: frames/s per $1,000 of MSRP
Top 15 shown; 15 more cards in the full table below.
Launch price, not street price, so it ages. A speed leaderboard always crowns the most expensive card; this is the counterweight.
Won't fit, LTX-Video gates these cards outright
| GPU | VRAM | Why it fails |
|---|---|---|
| NVIDIA GeForce RTX 3060 | 12GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 3080 Ti | 12GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 4070 Super | 12GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 4070 Ti | 12GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 4070 | 12GB | Needs ~14GB VRAM |
| GeForce RTX 5070 | 12GB | Needs ~14GB VRAM |
| NVIDIA TITAN V | 12GB | Needs ~14GB VRAM |
| NVIDIA TITAN X (Pascal) | 12GB | Needs ~14GB VRAM |
| NVIDIA TITAN Xp | 12GB | Needs ~14GB VRAM |
| GeForce GTX 1080 Ti | 11GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 2080 Ti Founders Edition | 11GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 3080 | 10GB | Needs ~14GB VRAM |
| NVIDIA GeForce GTX 1070 Ti | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce GTX 1080 | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 2060 Super | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 2070 SUPER | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 2070 | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 2080 Super | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 2080 Founders Edition | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 3050 | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 3060 Ti | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 3070 Ti | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 3070 Founders Edition | 8GB | Needs ~14GB VRAM |
| GeForce RTX 4060 | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 5050 | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 5060 | 8GB | Needs ~14GB VRAM |
| NVIDIA GeForce GTX 1660 Super | 6GB | Needs ~14GB VRAM |
| NVIDIA GeForce GTX 1660 Ti | 6GB | Needs ~14GB VRAM |
| NVIDIA GeForce GTX 1660 | 6GB | Needs ~14GB VRAM |
| NVIDIA GeForce RTX 2060 | 6GB | Needs ~14GB VRAM |
| NVIDIA RTX A2000 | 6GB | Needs ~14GB VRAM |
No driver update fixes a VRAM ceiling.
Full LTX-Video leaderboard, every card that runs it
| GPU | Result | VRAM | Source |
|---|---|---|---|
| NVIDIA B300 | 31.87 frames/s | 288GB | Measured |
| NVIDIA B200 | 26.8 frames/s | 192GB | Measured |
| NVIDIA B100 | 21.44 frames/s | 192GB | Estimated |
| NVIDIA GH200 Grace Hopper | 17.87 frames/s | 141GB | Estimated |
| NVIDIA H200 | 17.87 frames/s | 141GB | Measured |
| NVIDIA H100 NVL | 17.47 frames/s | 94GB | Estimated |
| NVIDIA H100 80GB HBM3 | 17.47 frames/s | 80GB | Measured |
| NVIDIA H800 80GB | 17.47 frames/s | 80GB | Estimated |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | 16.36 frames/s | 96GB | Measured |
| NVIDIA RTX PRO 6000 Blackwell Server Edition | 15.64 frames/s | 96GB | Measured |
| NVIDIA H100 PCIe | 15.09 frames/s | 80GB | Estimated |
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | 12.76 frames/s | 96GB | Estimated |
| NVIDIA GeForce RTX 5090 | 10.45 frames/s | 32GB | Measured |
| NVIDIA A100 40GB SXM4 | 8.95 frames/s | 40GB | Estimated |
| NVIDIA A100 80GB SXM4 | 8.95 frames/s | 80GB | Measured |
| NVIDIA A800 80GB | 8.95 frames/s | 80GB | Estimated |
| NVIDIA A100 40GB PCIe | 8.51 frames/s | 40GB | Estimated |
| NVIDIA A100 80GB PCIe | 8.51 frames/s | 80GB | Measured |
| NVIDIA L40S | 8.01 frames/s | 48GB | Measured |
| NVIDIA GeForce RTX 4090 | 6.7 frames/s | 24GB | Measured |
| NVIDIA RTX PRO 5000 Blackwell | 4.58 frames/s | 48GB | Measured |
| GeForce RTX 5080 | 4.33 frames/s | 16GB | Measured |
| NVIDIA GeForce RTX 4080 | 3.71 frames/s | 16GB | Measured |
| NVIDIA RTX PRO 4500 Blackwell | 3.58 frames/s | 32GB | Measured |
| NVIDIA RTX A5500 | 3.31 frames/s | 24GB | Estimated |
| NVIDIA RTX 5000 Ada Generation | 3.23 frames/s | 32GB | Measured |
| NVIDIA GeForce RTX 3090 Ti | 3.2 frames/s | 24GB | Measured |
| NVIDIA RTX PRO 4000 Blackwell | 3.1 frames/s | 24GB | Measured |
| GeForce RTX 4080 Super | 2.85 frames/s | 16GB | Measured |
| GeForce RTX 5070 Ti | 2.79 frames/s | 16GB | Measured |
| NVIDIA GeForce RTX 4070 Ti Super | 2.77 frames/s | 16GB | Measured |
| NVIDIA RTX A5000 | 2.7 frames/s | 24GB | Measured |
| NVIDIA L40 | 2.61 frames/s | 48GB | Measured |
| NVIDIA RTX 5880 Ada Generation | 2.49 frames/s | 48GB | Estimated |
| NVIDIA RTX A4500 | 2.39 frames/s | 20GB | Measured |
| NVIDIA RTX A4000 | 2.32 frames/s | 16GB | Measured |
| NVIDIA GeForce RTX 3090 | 2.17 frames/s | 24GB | Measured |
| NVIDIA RTX 4000 (Ada Generation) | 2.06 frames/s | 20GB | Measured |
| NVIDIA RTX 4500 Ada Generation | 1.94 frames/s | 24GB | Estimated |
| NVIDIA Quadro RTX 5000 | 1.88 frames/s | 16GB | Estimated |
| GeForce RTX 5060 Ti | 1.71 frames/s | 16GB | Measured |
| NVIDIA GeForce RTX 4060 Ti 16GB | 1.67 frames/s | 16GB | Measured |
| NVIDIA RTX 2000 Ada Generation | 1.39 frames/s | 16GB | Measured |
Tap any column to sort. Measured = we rented and ran this card ourselves. Estimated = interpolated against our measured anchors, never blended silently.
Because this workload is tensor-compute bound, the ranking tracks architecture generation and tensor throughput rather than memory bandwidth, the reverse of our LLM charts. The same two cards can swap places entirely depending on which of these pages you're reading. That's the reason we run twelve workloads instead of publishing one score. A GPU isn't fast or slow. It's fast at some things and gated out of others, and which of those matters depends entirely on what you're actually going to run.
NVIDIA B300 tops our LTX-Video leaderboard at 31.87 frames/s (measured), 2193% of the way clear of the slowest card that still fits. But the number that decides most purchases isn't on the chart. It's the 31 cards that can't run LTX-Video at all. This is a compute workload: buy architecture generation, not raw VRAM, as long as you clear the floor first.
Every ranking on this page comes from our own benchmark runs, not vendor claims. Cards marked Measured were rented and run by us; cards marked Estimated are interpolated per workload against those measured anchors and are labelled on every row, we never blend the two silently. LLMs run on llama.cpp (llama-bench) at Q4_K_M with -p 512 -n 128. Diffusion and video run on diffusers/ComfyUI at BF16, with SDXL at FP16. Each workload gets a warmup pass plus multiple timed runs (5 for small LLMs, 3 for large models and images, 2 for video); we publish the mean as the result and the minimum as the 1% low. Run-to-run variance is under 0.5%. Telemetry, power, temperature, utilisation, clocks, peak VRAM, is sampled at 1 Hz for the duration of every run. Where a model exceeds a card's VRAM we publish a hard won't-fit result rather than quietly dropping to a smaller quantisation. A card that can't run a model scores zero on it. Silently swapping precision to make a number appear would make every number on this site meaningless. All figures are single-GPU, single-stream, batch-size-1. That is the honest way to measure what one card does for one user, and it is deliberately not how a datacenter serves a model. Vendor and MLPerf figures use large batches across many GPUs and will be far higher. Neither is wrong, they answer different questions. Ours answers 'what will this card do for me'.