enso/MODEL_CARD.md

language, license, library_name, pipeline_tag, tags, metrics, model-index

language	license	library_name	pipeline_tag	tags	metrics	model-index
en multilingual	proprietary	hanzo	text-generation	intelligent-routing router dynamic-inference llm-orchestration api-only	routing_accuracy token_savings latency_overhead	name results hanzoai/enso-auto task metrics type name text-generation Dynamic Model Routing type value name accuracy 0.962 Tier Selection Accuracy type value name cost_reduction 0.684 Average Cost Savings vs Frontier type value name latency_ms 14.8 Router Latency Overhead

Enso: Intelligent Routing & Multi-Tier Intelligence Model Card

⚠️ API-only · Weights not distributed
Enso is Hanzo AI's dynamic routing engine and intelligent multi-tier frontier system.
Endpoint: https://api.hanzo.ai/v1/chat/completions

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1. Overview & Tier Taxonomy

Enso analyzes incoming prompts (tokens, complexity, intent, tool requirements) and dynamically routes execution to the optimal intelligence tier:

Model ID	Target Workload	Latency Profile	Relative Cost	Context Window
enso-ultra	Complex multi-step reasoning, theorem proving, architecture synthesis	Standard	Frontier	Up to 1M tokens
enso-pro	Production software engineering, drafting, analytical synthesis	Fast	Balanced (35% of Ultra)	Up to 256K tokens
enso-flash	High-throughput agents, real-time chat, structured extractions	Ultra-Fast (<15ms)	Low (5% of Ultra)	Up to 128K tokens
enso-auto	Autonomous router choosing between Flash, Pro, and Ultra per request	Dynamic	Optimized (~68% savings)	Up to 1M tokens
enso-free	Open community tier across open-weight models	High-Throughput	Zero cost	Up to 32K tokens

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2. Router Benchmarks & Economics

Evaluated across 50,000 multi-domain requests (MMLU-Pro, SWE-bench, Math, Chat):

Metric	Enso Auto	Always Frontier (GPT-4o / Claude 3.5 Sonnet)	Always Small (8B)
Composite Quality Score	94.8%	95.2%	71.4%
Average Cost per 1M Tokens	$1.14	$4.85	$0.20
Median Time-to-First-Token	180 ms	620 ms	140 ms
Router Decision Overhead	14.8 ms	N/A	N/A

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3. Quickstart Integration

from openai import OpenAI

client = OpenAI(
    api_key="your-hanzo-api-key",
    base_url="https://api.hanzo.ai/v1"
)

response = client.chat.completions.create(
    model="enso-auto",
    messages=[
        {"role": "user", "content": "Analyze the time complexity of this distributed consensus algorithm."}
    ]
)
print(response.choices[0].message.content)

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4. Hub & Documentation Links

• Documentation: docs.hanzo.ai/docs/models/enso
• Hugging Face Hub: huggingface.co/hanzoai/enso-auto
• Interactive Router Space: huggingface.co/spaces/hanzoai/enso-router