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undi95 · Open weights

ReMM SLERP 13B

Added Jan 1, 2024Open weights

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Use in the app

A recreation trial of the original MythoMax-L2-B13 but merged with updated models.

  • PDF input
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.80
Output
$1.21

Reference prices as published by the model provider. API example

Specifications

Context window
6.1K
Max output
4.1K
Average output (7 days)
62 tokens
Longer than 5% of 468 models

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ReMM SLERP 13B compared

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

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ReMM SLERP 13Bundi95This modelEVA-Qwen2.5-72B-v0.2eva-unit-01Remove
Providerundi95eva-unit-01
Discovery tierOpen weightsOpen weights
AddedJan 1, 2024Sep 25, 2025
Limits
Context window6.14K16.38KBest
Max output4.1K8.19KBest
Average output62 tokens306 tokens
Pricing, USD per 1M tokens
Input$0.80$0.80
Output$1.21$0.80Best
Performance
Request success (24h)—12.8%
Capabilities
PDF inputYesNo
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": "undi95/remm-slerp-l2-13b",
    "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="undi95/remm-slerp-l2-13b",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)