Wan2.1-T2V-14B (Turbo)
Tentang Wan2.1-T2V-14B (Turbo)
Wan2.1-T2V-14B-T adalah versi dipercepat dari TeaCache dari model Wan2.1-T2V-14B, mengurangi waktu pembuatan video tunggal sebesar 30%. Model Wan2.1-T2V-14B telah menetapkan patokan kinerja mutakhir di antara model sumber terbuka dan tertutup, mampu menghasilkan konten visual berkualitas tinggi dengan efek dinamis yang signifikan. Ini adalah satu-satunya model Video yang dapat secara simultan menghasilkan Text dalam bahasa Cina dan Inggris, dan mendukung pembuatan Video pada resolusi 480P dan 720P. Model ini mengadopsi arsitektur transformator difusi dan meningkatkan kemampuan generatifnya melalui variational autoencoder (VAE) spatiotemporal inovatif, strategi pelatihan yang dapat diskalakan, dan konstruksi data berskala besar.
Explore how DeepSeek-V3's advanced reasoning and coding capabilities translate into real-world applications.
Automated Code Generation & Debugging
Generate, optimize, and debug complex code snippets across various programming languages. The model's strong reasoning helps identify logical errors and suggest efficient solutions.
Use Case Example:
"A software engineer used DeepSeek-V3 to refactor a legacy Python module, resulting in a 40% reduction in code complexity and a 25% improvement in execution speed."
Scientific & Mathematical Research
Assist researchers by solving complex mathematical problems, formulating hypotheses, and analyzing data. Its ability to reason through abstract concepts makes it a powerful tool for scientific discovery.
Use Case Example:
"A physicist modeled a complex quantum mechanics problem, and the model provided a step-by-step derivation that led to a novel insight, which was later verified experimentally."
Intelligent Agent & Tool Integration
Build sophisticated AI agents that can understand user requests, select the appropriate tools (e.g., APIs, databases), and execute multi-step tasks autonomously.
Use Case Example:
"An automated travel assistant powered by DeepSeek-V3 booked a complete itinerary by interacting with flight, hotel, and car rental APIs based on a single natural language request from the user."
Advanced Conversational AI
Create highly engaging and context-aware chatbots, virtual assistants, or role-playing characters for gaming and entertainment. The model excels at maintaining coherent and natural-sounding dialogue.
Use Case Example:
"A gaming company implemented an NPC (Non-Player Character) using the model, which provided dynamic, unscripted interactions that significantly enhanced player immersion."
Metadata
Spesifikasi
Negara
Deprecated
Arsitektur
Terkalibrasi
Tidak
Campuran Ahli
Tidak
Total Parameter
14B
Parameter yang Diaktifkan
Penalaran
Tidak
Precision
FP8
Text panjang konteks
0K
Max Tokens
Bandingkan dengan Model Lain
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Total Context:
262K
Max output:
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Input:
$
0.2
/ M Tokens
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0.6
/ M Tokens
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Max output:
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Input:
$
0.18
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Total Context:
262K
Max output:
262K
Input:
$
0.18
/ M Tokens
Output:
$
2.0
/ M Tokens
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Total Context:
262K
Max output:
262K
Input:
$
0.3
/ M Tokens
Output:
$
1.5
/ M Tokens
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Total Context:
262K
Max output:
262K
Input:
$
0.45
/ M Tokens
Output:
$
3.5
/ M Tokens
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Qwen3-VL-30B-A3B-Instruct
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Total Context:
262K
Max output:
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Input:
$
0.29
/ M Tokens
Output:
$
1.0
/ M Tokens
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Total Context:
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Max output:
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Input:
$
0.29
/ M Tokens
Output:
$
1.0
/ M Tokens
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$
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