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Nexus Neural Models & API Specifications

High-efficiency AI model family engineered for high-throughput enterprise tasks, zero-retention privacy, and sub-10ms inference.

Nexus-LLM-70B

TEXT / CODE

70-billion parameter transformer trained on 4 Trillion tokens of code, mathematical proofs, and technical whitepapers.

Context 128K

Speed 142 t/s

AWQ 4-Bit

Vision-Transformer-X

MULTI-MODAL

High-precision visual spatial reasoning model capable of analyzing 4K imagery and 120fps video streams in real-time.

Latency 4.1ms

Input 4K Image/Video

Objects 200+ Class

Quantum-Embedder

VECTOR ENGINE

1536-dimensional neural embedding algorithm providing state-of-the-art semantic search across unstructured data stores.

Dimensions 1536D

Speed 1.4ms

Recall 99.9%

API_INTEGRATION_CODE_SNIPPET.PY

// Python SDK Quickstart:

import nexus_ai client = nexus_ai.Client(api_key="nx_live_998877665544332211") response = client.models.generate( model="Nexus-LLM-70B", prompt="Synthesize quantum routing algorithm for neural cluster", temperature=0.2, max_tokens=512 ) print(response.output_text) # Output: [SUCCESS] Tokens generated in 7.8ms