Mistral Large 2: The 128K Context Enterprise LLM from Europe

A European Alternative to US Frontier Models

Mistral Large 2 is Mistral AI's flagship model: 123 billion parameters, 128k token context, native function calling, and strong multilingual capability across 80+ languages including French, German, Spanish, Italian, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese, and Korean.

For European enterprises with data residency requirements, Mistral offers self-hosted deployment options alongside the Mistral AI API - something neither OpenAI nor Anthropic currently match at this model quality tier.

Key Benchmarks

HumanEval at 92% makes it competitive with GPT-4o for code generation at less than half the price.

Pricing and API

Via the Mistral AI API: $2.00 per million input tokens, $6.00 per million output tokens. That's 20% cheaper than GPT-4o on input.

pip install mistralai

from mistralai import Mistral

client = Mistral(api_key="your-mistral-api-key")

response = client.chat.complete(
    model="mistral-large-latest",
    messages=[
        {"role": "user", "content": "Write a TypeScript function to debounce API calls."}
    ]
)
print(response.choices[0].message.content)

Parallel Function Calling

Mistral Large 2 supports parallel function calls - critical for agentic workflows where multiple tool calls can execute simultaneously:

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get weather for a city",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {"type": "string"}
                },
                "required": ["city"]
            }
        }
    }
]

response = client.chat.complete(
    model="mistral-large-latest",
    messages=[{"role": "user", "content": "What's the weather in Paris and Berlin?"}],
    tools=tools,
    tool_choice="auto"
)

Self-Hosting

Model weights are available on HuggingFace under a research license. For production self-hosting, deploy with vLLM on 2-4× A100 80GB GPUs:

pip install vllm
python -m vllm.entrypoints.openai.api_server     --model mistralai/Mistral-Large-Instruct-2407     --tensor-parallel-size 4

When to Use Mistral Large 2

• Multilingual applications serving European or Asian markets
• Enterprises requiring on-premises deployment
• Code generation and analysis at $2/1M input cost
• Applications needing strong instruction following without GPT-4o pricing

Summary

Mistral Large 2 is a compelling choice for code-heavy or multilingual enterprise applications, particularly where European data sovereignty matters. Access it via the Mistral AI API or self-host from HuggingFace.