Mixtral 8x22B - Oxen.ai

Try Mixtral 8x22B in the Workbench

Run this model interactively, tune parameters, and compare outputs.

Model ID: open-mixtral-8x22b Mixtral-8x22B is an LLM that excels in multilingual support across English, French, Italian, German, and Spanish, as well as strong capabilities in mathematics and coding tasks. It utilizes a Sparse Mixture of Experts architecture, offering efficient performance with 39 billion active parameters out of 141 billion. Some noteworthy use cases of Mixtral-8x22B include handling multilingual tasks and performing complex mathematical computations.

Metric	Value
Parameter Count	141 billion
Mixture of Experts	Yes
Active Parameter Count	39 billion
Context Length	64,000 tokens
Multilingual	Yes
Quantized*	Unknown

*Quantization is specific to the inference provider and the model may be offered with different quantization levels by other providers.

Example request

Use the Workbench as a request builder: configure parameters for this model in the UI, then open the API tab to copy the exact cURL or Python call.

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Basic parameters
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curl -X POST https://hub.oxen.ai/api/ai/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "open-mixtral-8x22b",
  "messages": [
    {
      "role": "user",
      "content": "Hello, what can you do?"
    }
  ]
}'

import os
import requests

response = requests.post(
    "https://hub.oxen.ai/api/ai/chat/completions",
    headers={
        "Content-Type": "application/json",
        "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
    },
    json={
        "model": "open-mixtral-8x22b",
        "messages": [
            {
                "role": "user",
                "content": "Hello, what can you do?"
            }
        ]
    },
)
response.raise_for_status()
print(response.json())

curl -X POST https://hub.oxen.ai/api/ai/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "open-mixtral-8x22b",
  "messages": [
    {
      "role": "user",
      "content": "Hello, what can you do?"
    }
  ],
  "temperature": 0.7,
  "max_tokens": 1024,
  "stream": false
}'

import os
import requests

response = requests.post(
    "https://hub.oxen.ai/api/ai/chat/completions",
    headers={
        "Content-Type": "application/json",
        "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
    },
    json={
        "model": "open-mixtral-8x22b",
        "messages": [
            {
                "role": "user",
                "content": "Hello, what can you do?"
            }
        ],
        "temperature": 0.7,
        "max_tokens": 1024,
        "stream": false
    },
)
response.raise_for_status()
print(response.json())

curl -X POST https://hub.oxen.ai/api/ai/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "open-mixtral-8x22b",
  "messages": [
    {
      "role": "user",
      "content": "Hello, what can you do?"
    }
  ],
  "temperature": 0.7,
  "max_tokens": 1024,
  "stream": false,
  "top_p": 1.0
}'

import os
import requests

response = requests.post(
    "https://hub.oxen.ai/api/ai/chat/completions",
    headers={
        "Content-Type": "application/json",
        "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
    },
    json={
        "model": "open-mixtral-8x22b",
        "messages": [
            {
                "role": "user",
                "content": "Hello, what can you do?"
            }
        ],
        "temperature": 0.7,
        "max_tokens": 1024,
        "stream": false,
        "top_p": 1.0
    },
)
response.raise_for_status()
print(response.json())

Fetch model details

The models endpoint returns the full model object, including its json_request_schema.

curl -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/ai/models/open-mixtral-8x22b

Request parameters

This model follows the standard OpenAI chat completions request body. See the chat completions reference for the full parameter list.

Try Mixtral 8x22B in the Workbench

​Example request

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Example request

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Request parameters