meganova · Efficient

Manta Pro 1.0

Added Sep 20, 2025

Use in the app

Tailored for deep reasoning, long-form generation, and RAG workloads. 32K token context window.

Input: Text
Output: Text
Discovery tier: Efficient

Pricing

USD per 1M tokens

Input: $0.06
Output: $0.50

Reference prices as published by the model provider. API example

Specifications

Context window: 65.5K
Max output: —
Average output (7 days): 198 tokens; Longer than 20% of 468 models

Side by side

Manta Pro 1.0 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

Limits
	Manta Pro 1.0meganovaThis model	Manta Flash 1.0meganovaRemove
Provider	meganova	meganova
Discovery tier	Efficient	Efficient
Added	Sep 20, 2025	Sep 20, 2025
Context window	65.54KBest	16.38K
Average output	198 tokens	191 tokens
Pricing, USD per 1M tokens
Input	$0.06	$0.02Best
Output	$0.50	$0.16Best
Performance
Throughput	—	73.1 tok/s
Time to first token	—	4.1 s
Request success (24h)	—	100.0%
Capabilities
Reasoning effort	—	—

Public evaluations

Benchmarks

There are no public benchmark results for these models yet.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart

curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meganova-ai/manta-pro-1.0",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="meganova-ai/manta-pro-1.0",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

meganova

Other meganova models, starting with the same family.