AI21: Jamba 1.5 Mini

ai21/jamba-1-5-mini

Created Aug 23, 2024256,000 context

$0.20/M input tokens$0.40/M output tokens

Jamba 1.5 Mini is the world's first production-grade Mamba-based model, combining SSM and Transformer architectures for a 256K context window and high efficiency.

It works with 9 languages and can handle various writing and analysis tasks as well as or better than similar small models.

This model uses less computer memory and works faster with longer texts than previous designs.

Read their announcement to learn more.

Providers for Jamba 1.5 Mini

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

Apps using Jamba 1.5 Mini

Top public apps this week using this model

Recent activity on Jamba 1.5 Mini

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Uptime stats for Jamba 1.5 Mini

Uptime stats for Jamba 1.5 Mini across all providers

Sample code and API for Jamba 1.5 Mini

OpenRouter normalizes requests and responses across providers for you.

OpenRouter provides an OpenAI-compatible completion API to 300+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

from openai import OpenAI

client = OpenAI(
  base_url="https://openrouter.ai/api/v1",
  api_key="<OPENROUTER_API_KEY>",
)

completion = client.chat.completions.create(
  extra_headers={
    "HTTP-Referer": "<YOUR_SITE_URL>", # Optional. Site URL for rankings on openrouter.ai.
    "X-Title": "<YOUR_SITE_NAME>", # Optional. Site title for rankings on openrouter.ai.
  },
  extra_body={},
  model="ai21/jamba-1-5-mini",
  messages=[
    {
      "role": "user",
      "content": "What is the meaning of life?"
    }
  ]
)
print(completion.choices[0].message.content)

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.