mistralai/mistral-large
Ngày phát hành: 2024-02-26
128,000 context · $2.00/M input tokens · $6.00/M output tokens
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....
Pricing
Pay-per-use
No upfront costs, pay only for what you use
Try the model
API Usage
Use the following code examples to integrate with our API:
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["WAVESPEED_API_KEY"],
base_url="https://llm.wavespeed.ai/v1",
timeout=120.0,
max_retries=2,
)
try:
response = client.chat.completions.create(
model="mistralai/mistral-large",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content or "")
except Exception as exc:
raise SystemExit(f"LLM request failed: {exc}") from excModel Introduction
Mistralai mistral-large
mistralai mistral-large
Why It Looks Great
- Large Language Model architecture for efficient processing
- 128000 context window for long document handling
- Competitive pricing at $2.2/$6.6 per million tokens
Key Features
- Context Window: 128000 tokens
- Max Output: 4096 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | Mistralai |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 128000 tokens |
| Max Output | 4096 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $2.2 |
| Output | $6.6 |
How to Use
- Write your prompt — describe the task, provide context, and specify desired output format.
- Submit — the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: mistralai/mistral-large
API Usage
Python SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="mistralai/mistral-large",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "mistralai/mistral-large",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: mistralai/mistral-large
- Provider: Mistralai
Info
Supported Functionality
API Access Guide
Mistral Large API
mistralai/mistral-large
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](https://mistral.ai/news/mistral-large-2407/)....
Input
$2 /M
Output
$6 /M
Context
128K
Max Output
4K
Tool Use
Supported
Try Mistral Large on WaveSpeedAI
Access Mistral Large through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about Mistral Large
How much does Mistral Large cost via the API?+
Pricing on WaveSpeedAI: $2.00 per million input tokens and $6.00 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of Mistral Large?+
Mistral Large supports up to 128K tokens of context with up to 4K tokens of output per request.
Is Mistral Large OpenAI-compatible?+
WaveSpeedAI exposes Mistral Large at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.
How do I get started with Mistral Large?+
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.