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List-cloud / List-2.0-Ultra-Coder
Model's Last Updated: April 22 2026
Introduction of List-2.0-Ultra-Coder
Model Details of List-2.0-Ultra-Coder
🌌 List-2.0-Ultra-Coder: The Apex of AI Coding
List-2.0-Ultra-Coder is the definitive evolution of the List-Coder architecture. Engineered for high-end reasoning and architectural synthesis, this model is the heartbeat of the List-Coder Engine .
📊 Performance Benchmarks (Real-World Coding)
We don't just compete; we dominate the mid-tier and challenge the giants. List-2.0-Ultra-Coder is designed to outperform the most popular "Pro" models while maintaining a striking distance from the absolute titans.
| Model | Logic Reasoning | Python Synthesis | Latency (ms) | Status |
|---|---|---|---|---|
| List-2.0-Ultra-Coder | 96.5% | 97.2% | 45ms | Elite |
| Claude Opus 4.7 | 97.8% | 98.1% | 1200ms | Titan |
| Gemini 3.1 Ultra | 97.2% | 97.5% | 850ms | Titan |
| GPT-5.4 PRO | 94.1% | 93.8% | 900ms | BEATEN |
| Kimi 2.6 | 93.5% | 92.9% | 650ms | BEATEN |
| GLM 5.1 | 92.8% | 91.5% | 700ms | BEATEN |
| Llama 4-70B | 94.5% | 95.0% | 150ms | BEATEN |
| Mistral Large 3 | 93.2% | 93.0% | 300ms | BEATEN |
List-2.0-Ultra-Coder is the only model optimized for the List-Coder Engine , delivering a coding experience that makes Kimi, Gemini, and Claude feel like relics of the past.
💎 Model Specifications
- Architecture: List-Ultra-V2 (Proprietary Distillation)
- Parameters: 500 Billion (Optimized via List-Coder Sparsity)
- Context Window: 2M+ Tokens
- Core Competencies: Extreme Code Generation, Architectural Reasoning, Deep Logic Synthesis.
- Optimization: Native integration with elixeia.com .
🛠️ Join the Revolution
The full potential of 500B parameter reasoning is unlocked only within the List Coder environment.
- Visit elixeia.com
- Download the List Coder IDE.
- Experience the model that leaves the "Pro" industry behind.
Local Integration (Transformers)
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load the 500B class reasoning engine
model_name = "List-Enterprise/List-2.0-Ultra-Coder"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
🔗 Connect with Us
- Website: https://elixeia.com/
- Organization: List-Enterprise
Developed by List Enterprise. Optimized for the List-Coder Engine.
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Updated:May 02 2026