Embeddings API

Transform text into powerful vector representations. Build semantic search, recommendations, clustering, and RAG applications with state-of-the-art embeddings.

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"Happy customer"

→

[0.23, 0.87, -0.45, ...]

"Satisfied client"

→

[0.21, 0.89, -0.42, ...]

"Broken product"

→

[-0.67, 0.12, 0.94, ...]

Why Our Embeddings?

Industry-leading quality with best-in-class performance.

🎯

High Accuracy

Top MTEB benchmark scores

⚡

Low Latency

<10ms average response

📏

Flexible Dimensions

256 to 3072 dimensions

💰

Cost Effective

$0.02 per 1M tokens

What Can You Build?

🔍

Semantic Search

Find relevant documents based on meaning, not just keywords. Search through documents, FAQs, and knowledge bases.

🤖

RAG Applications

Retrieval-Augmented Generation: ground LLM responses in your own data for accurate, up-to-date answers.

💡

Recommendations

Surface similar products, articles, or content based on semantic similarity.

📊

Clustering

Group similar documents, support tickets, or feedback into meaningful categories.

🔄

Duplicate Detection

Find near-duplicates in large datasets, detect plagiarism, or deduplicate content.

😊

Sentiment Analysis

Classify text by sentiment, intent, or topic using embedding similarity.

Get Started in Seconds

                Python
            

                from mythicdot import MythicDot

client = MythicDot()

# Generate embeddings for a single text
response = client.embeddings.create(
    model="mythic-embed-3",
    input="The quick brown fox jumps over the lazy dog"
)

embedding = response.data[0].embedding
print(f"Dimensions: {len(embedding)}")  # 1536

# Batch embeddings for multiple texts
texts = [
    "How do I reset my password?",
    "I forgot my login credentials",
    "What's your return policy?"
]

batch_response = client.embeddings.create(
    model="mythic-embed-3",
    input=texts
)

for i, item in enumerate(batch_response.data):
    print(f"Text {i+1}: {len(item.embedding)} dimensions")
            

Model	Dimensions	Max Tokens	Price / 1M tokens
mythic-embed-3 RECOMMENDED	1536	8,191	$0.02
mythic-embed-3-large	3072	8,191	$0.13
mythic-embed-lite	256	512	$0.01

Performance at Scale

<10ms

Avg. latency

1M+

Texts per minute

99.9%

Uptime SLA

#1

MTEB ranking