Lightricks
LTX-2.3 Pro
Lightricks’ production video model — 4K output, synchronized audio and multi-shot control.
Intelligenza
89.1 #20
AAQI 89.0
Velocità Uscita
18 t/s
ITL 55.6 ms/tok
Prezzo combinato (3:1)
$0.12 /1M
Input $0.12/M · Output $0.12/M
Contesto
64K
≈ 160 pagine A4 · output max 2,048
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
LTX-2.3 Pro
Claude Mythos Preview (#1)
Average (68)
Gli assi radar sono approssimati dai punteggi di categoria dove mancano misurazioni dirette — vedi Metodologia.
Punti di forza e compromessi
Dove vince
- 4K + audio in a single pass — unique in class
- Multi-shot consistency for narrative content
- Precise camera and keyframe control
A cosa fare attenzione
- Pro-tier pricing per clip
- Closed weights — API only
- Queue latency at peak hours
Casi d'uso killer
Production video pipelines
4K deliverables with baked audio for ads and shorts.
Multi-shot storytelling
Character-consistent sequences for narrative clips.
Post-production assists
Extend/reframe existing footage with keyframe control.
Quickstart per sviluppatori e API
Imposta prima
OPENROUTER_API_KEY — ottieni una chiave APIcurl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "lightricks/ltx-2-3-pro",
"messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=os.environ["OPENROUTER_API_KEY"],
)
resp = client.chat.completions.create(
model="lightricks/ltx-2-3-pro",
messages=[{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}],
)
print(resp.choices[0].message.content)const res = await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
"content-type": "application/json",
},
body: JSON.stringify({
model: "lightricks/ltx-2-3-pro",
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).choices[0].message.content);OpenRouter-compatible endpoint — one API for 300+ models.
Risorse e link ufficiali
Deployment API
Confronta host e latenza
Throughput, TTFT e prezzi cache su Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock e Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Punteggi per Fonte
Punteggi per Categoria
Risultati dei Benchmark
Scontri diretti live
Specifiche live e architettura
Sotto il cofano
LTX-2.3 Pro — video foundation model
- Native 4K generation with synchronized audio track
- Multi-shot sequencing — keeps characters consistent across cuts
- Camera-path and keyframe conditioning for directors
- Frame-accurate edit and extend modes
Data di Rilascio
8 ott 2026
Architettura
LTX-2.3 Pro — video foundation model
Parametri
Not disclosed
Licenza
Proprietary
Finestra di Contesto
64,000 tokens
Output max
2,048 tokens
Modalità
text + video
Prezzi cache
lettura $0.02 · scrittura $0.12 /1M
Ragionamento
—
Prezzo Ingresso
$0.12/M
Prezzo Uscita
$0.12/M
Velocità Uscita
18 t/s
Tempo al Primo Token
—
Dati aggiornati
22 ott 2026
Stima bolletta mensile
Spesa mensile stimata
$0.00
Calcolo risparmio vs GPT-4o…
Cita e incorpora
Badge Markdown GitHub
Loading badge markdown...BibTeX
@misc{llmpodium2026ltx23pro,
title = {Benchmark Analysis and Intelligence Evaluation of LTX-2.3 Pro},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/ltx-2-3-pro}
}Incorpora il badge del punteggio
Aggiungi un badge Podium Score live al tuo README su GitHub o Hugging Face — rimanda alla classifica live.
Anteprima
Markdown
Loading badge snippet...HTML
Loading badge snippet...Altri modelli di Lightricks
Modelli alternativi
Migliori alternative a LTX-2.3 Pro in base a capacità, prezzi e benchmark.