Mistral Large 2407

mistralai/mistral-large-2407

This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement here....

Modalities: text+file->text
In / out price: $2 / $6per 1M
Context: 131K
Released: Nov 19, 2024
Knowledge cutoff: 2024-03-31

Providers

Every request enters through InfAPI. One key calls every model in the catalog. Upstream groups, ratios, and tiers are not shown.

Endpoint	Input	Output	Context	Status
InfAPI	$2	$6	131K	Available

Input: Text, File
Output: Text
Tokenizer: Mistral
Max output: 104,857
Endpoint: Chat

Pricing

Listed price for this model on this gateway. Token prices are per 1M tokens.

Item	Price	Unit
Inputprompt	$2	per 1M tokens
Outputcompletion	$6	per 1M tokens
Cache readinput_cache_read	$0.2	per 1M tokens

API

The gateway speaks the OpenAI Chat Completions API. Point any compatible SDK at https://infapi.cc/v1 and send the model slug below.

Get your API key

Create a key on the keys page and set it as an environment variable: Keys

shell

export INFAPI_API_KEY=sk-...

Make your first request

Use mistralai/mistral-large-2407

Python

import requests

response = requests.post(
    "https://infapi.cc/v1/chat/completions",
    headers={
        "Authorization": "Bearer $INFAPI_API_KEY",
        "Content-Type": "application/json",
    },
    json={
        "model": "mistralai/mistral-large-2407",
        "messages": [
            {
                "role": "user",
                "content": "Introduce yourself in three sentences."
            }
        ],
        "temperature": 0.3,
        "max_tokens": 512
    },
)
response.raise_for_status()
print(response.json()["choices"][0]["message"]["content"])

Endpoint

POST https://infapi.cc/v1/chat/completions

Authorization: Bearer $INFAPI_API_KEY

Using third-party SDKs

Point the OpenAI SDK at https://infapi.cc/v1 with $INFAPI_API_KEY. The HTTP samples above are the request shape this gateway accepts.

Python (OpenAI)

from openai import OpenAI

client = OpenAI(
    base_url="https://infapi.cc/v1",
    api_key="$INFAPI_API_KEY",
)

response = client.chat.completions.create(
    model="mistralai/mistral-large-2407",
    messages=[{"role": "user", "content": "Introduce yourself in three sentences."}],
    temperature=0.3,
    max_tokens=512,
)
print(response.choices[0].message.content)

TypeScript (OpenAI)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://infapi.cc/v1",
  apiKey: "$INFAPI_API_KEY",
});

const response = await client.chat.completions.create({
  "model": "mistralai/mistral-large-2407",
  "messages": [
    {
      "role": "user",
      "content": "Introduce yourself in three sentences."
    }
  ],
  "temperature": 0.3
});

console.log(response.choices[0]?.message?.content);

Supported parameters

frequency_penalty
Frequency penalty
Lowers the chance of a token in proportion to how often it already appeared.
max_tokens
Max tokens
Upper bound on generated tokens. Output stops at the limit.
presence_penalty
Presence penalty
Lowers the chance of any token that has already appeared.
response_format
Response format
For example json_object or json_schema, to constrain the shape.
seed
Seed
A fixed seed helps reproduce sampling. It does not guarantee byte-identical output.
stop
Stop
Stop when these strings are produced. A string or an array of strings.
structured_outputs
Structured outputs
Generate a parseable structure that follows a JSON Schema.
temperature
Temperature
Sampling temperature. Lower is steadier, higher is more varied. Often 0 to 2.Default 0.3
tool_choice
Tool choice
Whether to call a tool: auto, none, or a named function.
tools
Tools
Function definitions the model may call via tool_calls.
top_p
Top-p
Sample only from tokens whose cumulative probability reaches top_p.

FAQ

What is this model?

This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning,…

How much does it cost?

$2 / $6

What inputs and outputs does it support?

text+file->text

When was it released?

Nov 19, 2024

Try this model

Endpoint

Input

Output

Context

Status

InfAPI

131K

Available

Item

Price

Unit

Inputprompt

per 1M tokens

Outputcompletion

per 1M tokens

Cache readinput_cache_read

$0.2

per 1M tokens

API

The gateway speaks the OpenAI Chat Completions API. Point any compatible SDK at https://infapi.cc/v1 and send the model slug below.

Get your API key

Create a key on the keys page and set it as an environment variable: Keys

shell

export INFAPI_API_KEY=sk-...

Make your first request

Use mistralai/mistral-large-2407

Python

import requests

response = requests.post(
    "https://infapi.cc/v1/chat/completions",
    headers={
        "Authorization": "Bearer $INFAPI_API_KEY",
        "Content-Type": "application/json",
    },
    json={
        "model": "mistralai/mistral-large-2407",
        "messages": [
            {
                "role": "user",
                "content": "Introduce yourself in three sentences."
            }
        ],
        "temperature": 0.3,
        "max_tokens": 512
    },
)
response.raise_for_status()
print(response.json()["choices"][0]["message"]["content"])

Endpoint

POST https://infapi.cc/v1/chat/completions

Authorization: Bearer $INFAPI_API_KEY

Using third-party SDKs

Point the OpenAI SDK at https://infapi.cc/v1 with $INFAPI_API_KEY. The HTTP samples above are the request shape this gateway accepts.

Python (OpenAI)

from openai import OpenAI

client = OpenAI(
    base_url="https://infapi.cc/v1",
    api_key="$INFAPI_API_KEY",
)

response = client.chat.completions.create(
    model="mistralai/mistral-large-2407",
    messages=[{"role": "user", "content": "Introduce yourself in three sentences."}],
    temperature=0.3,
    max_tokens=512,
)
print(response.choices[0].message.content)

TypeScript (OpenAI)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://infapi.cc/v1",
  apiKey: "$INFAPI_API_KEY",
});

const response = await client.chat.completions.create({
  "model": "mistralai/mistral-large-2407",
  "messages": [
    {
      "role": "user",
      "content": "Introduce yourself in three sentences."
    }
  ],
  "temperature": 0.3
});

console.log(response.choices[0]?.message?.content);

Supported parameters

frequency_penalty
Frequency penalty
Lowers the chance of a token in proportion to how often it already appeared.
max_tokens
Max tokens
Upper bound on generated tokens. Output stops at the limit.
presence_penalty
Presence penalty
Lowers the chance of any token that has already appeared.
response_format
Response format
For example json_object or json_schema, to constrain the shape.
seed
Seed
A fixed seed helps reproduce sampling. It does not guarantee byte-identical output.
stop
Stop
Stop when these strings are produced. A string or an array of strings.
structured_outputs
Structured outputs
Generate a parseable structure that follows a JSON Schema.
temperature
Temperature
Sampling temperature. Lower is steadier, higher is more varied. Often 0 to 2.Default 0.3
tool_choice
Tool choice
Whether to call a tool: auto, none, or a named function.
tools
Tools
Function definitions the model may call via tool_calls.
top_p
Top-p
Sample only from tokens whose cumulative probability reaches top_p.