Last refreshed 2026-06-01. Next refresh: weekly.
Why use MythoMax L2 13B on Fireworks AI?
Fireworks AI offers MythoMax L2 13B with pay-as-you-go pricing at $0.20/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare MythoMax L2 13B across 6 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport FIREWORKS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],accounts/fireworks/models/mythomax-l2-13bRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/mythomax-l2-13b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/mythomax-l2-13b", not the LLMReference slug "mythomax-l2-13b".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Compare MythoMax L2 13B Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Together AI | $0.30 | $0.30 |
| Lepton AI API | $0.13 | $0.13 |
| Fireworks AI | $0.20 | $0.20 |
| OpenRouter | $0.06 | $0.06 |
| Novita AI | $0.09 | $0.09 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About MythoMax L2 13B
MythoMax L2 13B is an advanced large language model developed by Gryphe, designed specifically for creative text generation, with a focus on storytelling and role-playing applications. It builds upon the Llama 2 architecture and utilizes a unique tensor merging technique that combines strengths from the MythoLogic-L2 and Huginn models. This enhances its ability to produce coherent, contextually relevant text for extended narratives and complex character interactions. The model features a substantial parameter count of 13 billion, supporting high-quality, fluent text generation.