MythoMax L2 13B

by Gryphe

Mythomax L2 13B is a 13-billion parameter open-weight model released by Gryphe in August 2023, built on Meta's Llama 2 foundation. It was designed to excel at creative writing and roleplay scenarios, combining emotional coherence with character consistency across long narrative exchanges. The model merges MythoLogic-L2 and Huginn using an experimental BlockMerge_Gradient tensor merging technique, where each of its 363 tensors received a unique blending ratio. This approach fuses one model's robust language understanding with another's narrative writing capability to produce strong results in both storytelling and character consistency. Mythomax L2 keeps persona traits, speech patterns, and emotional nuance steady across thousands of tokens without drifting into generic assistant-speak. It resists breaking character in complex roleplay scenarios and sustains emotional coherence in dialogue-driven narratives. The model uses Alpaca prompt formatting, and community quantizations in GGUF, GPTQ, and AWQ formats provide flexibility across varied hardware constraints.

Key info

Input
Output
Features
Context window
4K
Max output
4K
Input price
$0.40 /1M
Output price
$0.40 /1M
  • onchain settlement available
  • US residency available
  • Zero data retention on pay-as-you-go
  • No training by default
  • no-KYC deposit available

Available routes

MythoMax L2 13B runs on 2 different routes through the qynio gateway. Compare residency, zero retention, and training posture at a glance β€” full data-handling detail per route below.

ProviderRegionZero data retentionTrainingInputOutput
USZero data retentionNo$0.40$0.40
EUNot by defaultNo$0.06$0.06

Uptime and availability

One of MythoMax L2 13B's 2 routes is on the monitoring board, so the figure below is that provider's availability rather than the model's.

100%route uptime, last 30 days
Its other routes aren't measured here yet.

Name a second model in the same request and the gateway tries it on retriable errors, so a busy hour never has to reach your users. .

Measured over the last 30 days from each provider's official status feed via StatusGator. Refreshed hourly. 1 further route is not on the board yet. See uptime for every provider qynio monitors.

Data handling per route

Each route hosting MythoMax L2 13B has its own privacy posture, residency, and no-KYC terms. Postures are maintained by qynio with a last-verification timestamp.

DeepInfra β€” United StatesπŸ‡ΊπŸ‡Έ

Zero data retention is on by default on Pay-as-you-go β€” no action required. No training on customer data. US; unknown; deposit available.

Zero data retention
On by default on Pay-as-you-go. Derived from the logging and moderation facts.
Training
No training on customer data.
Logging
None
Moderation
Not established
Caching
Not established
Subprocessor access
Not established
no-KYC deposit
deposit available
Transfer mechanism
unknown

Nextbit β€” SpainπŸ‡ͺπŸ‡Έ

Zero data retention is not on by default β€” provider logging, 90-day retention. No training on customer data. EEA; wallets; deposit available.

Zero data retention
Not by default β€” provider logging, 90-day retention. Derived from the logging and moderation facts.
Training
No training on customer data.
Logging
Other (90-day retention)
Moderation
Not established
Caching
Not established
Subprocessor access
Not established
no-KYC deposit
deposit available
Transfer mechanism
wallets

Get started

Call MythoMax L2 13B through the qynio gateway with one API key. Let your coding agent set it up, or call it directly β€” qynio is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.

Set it up with your agent

Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up qynio for you.

Or call it directly

import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.QYN_API_KEY,
baseURL: "https://api.qyn.io/v3/compat",
});
const completion = await client.chat.completions.create({
model: "deepinfra/Gryphe/MythoMax-L2-13b",
messages: [{ role: "user", content: "Hello" }],
});
console.log(completion.choices[0].message.content);

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