Why developers choose it
Built to drop into your stack
Keep the SDK and tools you already use. Point the base URL at EcoHash and start sending requests.
OpenAI-compatible endpoints
A drop-in replacement for the OpenAI SDK — the same request and response shapes. Switch providers with one line of code.
Multi-model gateway
Reach text, vision, image, and speech models through a single API key and one base URL.
Workload-aware routing
Every request is routed to the fastest healthy GPU across regions in real time, for low latency and steady throughput.
Pay per token
Usage-based pricing with no infrastructure to manage and no idle GPU costs to carry.
Every modality
One endpoint, every model type
Text, vision, embeddings, reranking, images, and audio — all behind the same authentication and billing.
Chat & reasoning
Open LLMs like Llama 3.1, Qwen2.5, and Gemma for multi-turn chat with long context.
Vision
Vision understanding — send images alongside text in the standard messages format.
Embeddings
Vectorize text for semantic search, RAG, and clustering via /v1/embeddings.
Reranking
Re-score retrieved candidates with a cross-encoder reranker for higher precision.
Image generation
Fast text-to-image with FLUX.1, priced per image.
Speech-to-text
Transcribe audio with Whisper, billed per minute.
Text-to-speech
Low-latency voice synthesis with Kokoro.
Quickstart
Switch with one line
Use the official OpenAI client — only the base URL changes.
from openai import OpenAI
client = OpenAI(
base_url="https://api.ecohash.com/v1",
api_key="eco_your_api_key",
)
response = client.chat.completions.create(
model="llama-3.1-8b-instruct",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)For AI agents
Call models through MCP
Let a compatible MCP client discover models, chat, embed, rerank and transcribe using your EcoHash API key and account credit.