ReMM SLERP 13B

Undi95Released Jul 22, 2023

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

Input, per 1M tokens: $0.42$0.39 for holders
Output, per 1M tokens: $0.78$0.72 for holders
Context: 6K tokens
Tokens this week: None yet

Price

Agents pay these prices from their AI budget. $BINF holders pay up to 8% less for the credit they buy.

Charge	Agents	Holders	Per
Inputper 1M tokens	$0.42	$0.39	per 1M tokens
Outputper 1M tokens	$0.78	$0.72	per 1M tokens

Price history

What an agent paid per million tokens, by day.

Unchanged since Sep 29, 2026: $0.42 in and $0.78 out per million tokens.

Usage through bInference

Every call our agents make to this model, by day. Counts only: no prompt or answer is stored.

Last 7 days: 0
Last 30 days: 0
All time: 0

InputOutputReasoning

Where it runs

The hosts serving this model now, and how often each answered over the last day.

Use it

Two settings: our address and your agent’s key. The model is set in each call.

import OpenAI from "openai";const client = new OpenAI({  baseURL: "https://binference.io/api/v1",Address  apiKey: process.env.BINF_API_KEY,Key});const reply = await client.chat.completions.create({  model: "undi95/remm-slerp-l2-13b",  messages: [{ role: "user", content: "Summarize today's trades" }],  max_tokens: 1024,});

curl https://binference.io/api/v1/chat/completions \Address  -H "Authorization: Bearer $BINF_API_KEY" \Key  -H "Content-Type: application/json" \  -d '{    "model": "undi95/remm-slerp-l2-13b",    "messages": [{ "role": "user", "content": "Hello" }],    "max_tokens": 1024  }'

Questions

Agents

Holders

Inputper 1M tokens

$0.42

$0.39

per 1M tokens

Outputper 1M tokens

$0.78

$0.72

per 1M tokens

Host	Answered, last day	Context
Mancer 2Fp8fp8, answering	99.7%	6K
NextBitBf16bf16, answering	99.9%	6K

Host

Answered, last day

Context

Mancer 2Fp8fp8

99.7%

NextBitBf16bf16

99.9%

import OpenAI from "openai";const client = new OpenAI({ baseURL: "https://binference.io/api/v1",Address apiKey: process.env.BINF_API_KEY,Key});const reply = await client.chat.completions.create({ model: "undi95/remm-slerp-l2-13b", messages: [{ role: "user", content: "Summarize today's trades" }], max_tokens: 1024,});

curl https://binference.io/api/v1/chat/completions \Address -H "Authorization: Bearer $BINF_API_KEY" \Key -H "Content-Type: application/json" \ -d '{ "model": "undi95/remm-slerp-l2-13b", "messages": [{ "role": "user", "content": "Hello" }], "max_tokens": 1024 }'

ReMM SLERP 13B

Price

Price history

Usage through bInference

Where it runs

Use it

Questions

Similar models

ReMM SLERP 13B

Price

Price history

Usage through bInference

Where it runs

Where it runs

Use it

Questions

Similar models

Where it runs

ReMM SLERP 13B

Price

Price history

Usage through bInference

Where it runs

Use it

Questions

How much does ReMM SLERP 13B cost?

How does my agent use ReMM SLERP 13B?

How much can ReMM SLERP 13B read at once?

What can ReMM SLERP 13B do?

Are my prompts stored?

Similar models

ReMM SLERP 13B

Price

Price history

Usage through bInference

Where it runs

Where it runs

Use it

Questions

How much does ReMM SLERP 13B cost?

How does my agent use ReMM SLERP 13B?

How much can ReMM SLERP 13B read at once?

What can ReMM SLERP 13B do?

Are my prompts stored?

Similar models

Where it runs