Powered by Ollama · Alphanso AI Infrastructure

Local AI Models,
Enterprise Grade

Alphanso Technology's private Ollama inference server — run powerful open-source LLMs with zero data leaving your environment.

BASE URL https://ollama.alphansolabs.in
◆ Visit Alphanso Labs Ollama Docs ↗
99.9%
Uptime SLA
<50ms
Avg. Latency
REST
API Compatible
Private
On-Premise
// Platform Features

Everything you need to run
local AI models at scale

Alphanso's Ollama server gives your team private, fast, and compliant access to open-source LLMs.

🔒
100% Private
All inference stays on-premise inside Alphanso's secure infrastructure. Your data never leaves the server.
⚡
Low Latency Inference
GPU-accelerated model serving with optimized quantization for fast response times across all model sizes.
🔌
OpenAI-Compatible API
Drop-in replacement for OpenAI SDK. Point your base_url to this server and you're live instantly.
🧠
Multiple Models
Run Llama 3, Mistral, Gemma, Phi-3, DeepSeek and more — switch models per request with zero config.
📡
REST & Streaming
Full streaming support via Server-Sent Events. Build real-time chat and generation apps with ease.
🛡️
GDPR Compliant
No telemetry. No cloud calls. Fully auditable inference stack managed by Alphanso Technology team.
// Available Models

Ready-to-use Models

Pre-loaded open-source models available on this server. Pull additional models anytime.

ModelSizeContextType
llama3.2 latest
3.2B
128K
Chat / Instruct
mistral 7B
7B
32K
Chat / Instruct
gemma3 12B
12B
128K
Multimodal
phi4 14B
14B
16K
Reasoning
deepseek-r1 8B
8B
64K
Reasoning
nomic-embed-text embed
137M
8K
Embeddings
// Quick Start

Connect in seconds

Use the Ollama REST API or any OpenAI-compatible SDK to start generating.

cURL 
# Generate a completion
curl https://ollama.alphansolabs.in/api/generate \
  -d '{
  "model": "llama3.2",
  "prompt": "Hello from Alphanso!",
  "stream": false
}'
Python · OpenAI SDK 
from openai import OpenAI

client = OpenAI(
  base_url="https://ollama.alphansolabs.in/v1",
  api_key="ollama"  # not required
)

res = client.chat.completions.create(
  model="llama3.2",
  messages=[
    {"role": "user",
     "content": "What is AI?"}
  ]
)
print(res.choices[0].message.content)
JavaScript · Fetch 
const res = await fetch(
  "https://ollama.alphansolabs.in/api/chat",
  {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify({
      model: "mistral",
      messages: [
        { role: "user", content: "Hello!" }
      ]
    })
  }
);
const data = await res.json();
List Models 
# List all available models
curl https://ollama.alphansolabs.in/api/tags

# Pull a new model
curl https://ollama.alphansolabs.in/api/pull \
  -d '{"name": "deepseek-r1:8b"}'

# Check server health
curl https://ollama.alphansolabs.in/api/version