meganova · Efficient
Manta Mini 1.0
Lightweight tier optimized for speed and cost.
- Input
- Text
- Output
- Text
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.02
- Output
- $0.16
Reference prices as published by the model provider. API example
Specifications
- Context window
- 8.2K
- Max output
- —
- Average output (7 days)
- 35 tokens
- Longer than 2% of 468 models
Side by side
Manta Mini 1.0 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Manta Mini 1.0meganovaThis model | Synth 2.5 Flash PreviewlucidityRemove | |
|---|---|---|
| Provider | meganova | lucidity |
| Discovery tier | Efficient | Efficient |
| Added | Sep 20, 2025 | Sep 5, 2026 |
| Limits | ||
| Context window | 8.19K | 30KBest |
| Average output | 35 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.02Best | $0.03 |
| Output | $0.16 | $0.10Best |
| Performance | ||
| Request success (24h) | 95.8% | — |
| Capabilities | ||
| Reasoning effort | — | — |
Public evaluations
Benchmarks
There are no public benchmark results for these models yet.
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Request success (24h)
- 95.8%
- Reliable
Hourly request success · last 72 hoursLowest hour 80.0%
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
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-mini-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-mini-1.0",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)meganova
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