Lightricks
LTX-2.3 Fast
Real-time variant of LTX-2.3 for rapid iteration, previews and interactive video workflows.
Intelligenza
86.2 #40
AAQI 86.0
Velocità Uscita
60 t/s
ITL 16.7 ms/tok
Prezzo combinato (3:1)
$0.05 /1M
Input $0.05/M · Output $0.05/M
Contesto
64K
≈ 160 pagine A4 · output max 2,048
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
LTX-2.3 Fast
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
- ~3× faster than the Pro tier
- Cheapest per-clip price in the LTX line
- Drop-in compatibility with Pro prompts
A cosa fare attenzione
- 1080p ceiling — no 4K or native audio
- Noticeable detail loss on complex motion
- Short clip lengths only
Casi d'uso killer
Interactive previz
Live prompt iteration for directors and editors.
Social content at scale
Bulk short clips where turnaround beats fidelity.
Pro-tier drafting
Storyboard in Fast, re-render finals on Pro.
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-fast",
"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-fast",
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-fast",
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
Specifiche live e architettura
Sotto il cofano
LTX-2.3 Fast — distilled video model
- Distilled sampler — draft clips in seconds, not minutes
- Same conditioning interface as the Pro tier
- Optimized for preview-then-upscale workflows
- Lower per-clip cost for high-volume iteration
Data di Rilascio
8 ott 2026
Architettura
LTX-2.3 Fast — distilled video model
Parametri
Not disclosed
Licenza
Proprietary
Finestra di Contesto
64,000 tokens
Output max
2,048 tokens
Modalità
text + video
Prezzi cache
lettura $0.01 · scrittura $0.05 /1M
Ragionamento
—
Prezzo Ingresso
$0.05/M
Prezzo Uscita
$0.05/M
Velocità Uscita
60 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{llmpodium2026ltx23fast,
title = {Benchmark Analysis and Intelligence Evaluation of LTX-2.3 Fast},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/ltx-2-3-fast}
}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 Fast in base a capacità, prezzi e benchmark.