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Mistral: Devstral Small 2505

Mistral: Devstral Small 2505

An innovative midtier language model, masterfully crafted by leading AI developers to streamline the integration of large language models into applications.

Context: 128 000 tokens
Output: 128 000 tokens
Modality:
Text
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FrameFrame

The Pinnacle of API Scalability & Real-Time LLM Integration

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Devstral Small 2505 is part of the well-known Mistral family. This model is specifically designed for production use, where real-time processing and generative AI features are essential. As an open-source, lightweight solution, Devstral Small 2505 improves performance while lowering the computational load found in other models. This makes it perfect for real-time applications and integration into generative AI systems.

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Key Features of Devstral Small 2505

Low Latency & High Efficiency

Devstral Small 2505 boasts remarkable low latency that ensures swift processing, crucial for real-time applications. With optimized throughput, it provides developers the efficiency required to maintain seamless operations.

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Extended Context & Alignment

This model offers an extensive context window which can handle more tokens than several peers in its class, enhancing its ability to maintain coherence in extended narratives. Coupled with reinforced alignment and safety standards, it minimizes bias, boosting reliability in diverse applications.
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Multilingual Capability

Supporting a diverse array of languages, Devstral Small 2505 is a multilingual gem that caters to global user bases, facilitating improved communication and automation across regional locales.

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Developer-Centric Deployment

Developers enjoy unparalleled flexibility with Devstral Small 2505, thanks to its adaptable deployment options. It integrates smoothly with various environments and development pipelines, promoting a seamless developer experience.

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Use Cases for Devstral Small 2505

Chatbots for SaaS and Customer Support

Leverage Devstral Small 2505 to build intuitive chatbots capable of understanding nuanced human interaction, enhancing user experience in customer support and SaaS environments.

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Code Generation for IDEs and AI Development Tools

With advanced coding skills, this model empowers developers to auto-generate code blocks, streamline code reviews, and foster greater productivity in integrated development environments (IDEs).

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Document Summarization for Legal Tech and Research

Deploy Devstral Small 2505 to condense complex legal documents and research papers into concise summaries, effectively speeding up information retrieval and decision-making processes.

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Workflow Automation for Internal Operations and CRM

Automate repetitive workflow processes with precision, utilizing Mistral: Devstral Small 2505 to generate reports, update CRM data, and optimize operational efficiency.

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Knowledge Base Search for Enterprise Data and Onboarding

Enhance enterprise knowledge base systems with sophisticated search capabilities that accelerate onboarding processes and empower employees with fast, relevant information retrieval.

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Why Use Devstral Small 2505 via AnyAPI.ai


AnyAPI.ai improves the usage experience of Devstral Small 2505 by providing a unified API that connects various large language models. It offers tools like one-click onboarding, which removes vendor lock-in and encourages flexibility with usage-based billing.

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With production-grade infrastructure and dedicated developer tools, AnyAPI.ai provides better value than other platforms like OpenRouter and AIMLAPI through improved provisioning, unified access, and full support and analytics.

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Start Using Devstral Small 2505 via API Today


Integrate Devstral Small 2505 via AnyAPI.ai and unlock unprecedented opportunities for developers, startups, and teams. Boost productivity, ensure swift chatbot and software development, and enhance operational processes effortlessly.

Sign up, get your API key, and launch in minutes to start transforming your AI-driven projects today.

Comparison with other LLMs

Model
Context Window
Multimodal
Latency
Strengths
Model
Mistral: Devstral Small 2505
Context Window
128k
Multimodal
No
Latency
Medium
Strengths
GitHub automation, dev agents, open LLMs
Get access
Model
Qwen: Qwen3 30B A3B Instruct 2507
Context Window
256k
Multimodal
No
Latency
Fast
Strengths
Ultra-long context, multilingual, aligned, efficient
Get access
Model
OpenAI: GPT-4 Turbo
Context Window
128k
Multimodal
Yes
Latency
Very High
Strengths
Production-scale AI systems
Get access
Model
Mistral: Codestral 2508
Context Window
256K
Multimodal
No
Latency
Optimized for speed & accuracy
Strengths
Superior code generation with enterprise integration
Get access

Sample code for 

Mistral: Devstral Small 2505

Python
JavaScript
Curl
import requests

url = "https://api.anyapi.ai/v1/chat/completions"

payload = {
    "stream": False,
    "tool_choice": "auto",
    "logprobs": False,
    "model": "devstral-small-2505",
    "messages": [
        {
            "role": "user",
            "content": "Hello"
        }
    ]
}
headers = {
    "Authorization": "Bearer AnyAPI_API_KEY",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
import requests url = "https://api.anyapi.ai/v1/chat/completions" payload = { "stream": False, "tool_choice": "auto", "logprobs": False, "model": "devstral-small-2505", "messages": [ { "role": "user", "content": "Hello" } ] } headers = { "Authorization": "Bearer AnyAPI_API_KEY", "Content-Type": "application/json" } response = requests.post(url, json=payload, headers=headers) print(response.json())
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Code is copied
const url = 'https://api.anyapi.ai/v1/chat/completions';
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer AnyAPI_API_KEY', 'Content-Type': 'application/json'},
  body: '{"stream":false,"tool_choice":"auto","logprobs":false,"model":"devstral-small-2505","messages":[{"role":"user","content":"Hello"}]}'
};

try {
  const response = await fetch(url, options);
  const data = await response.json();
  console.log(data);
} catch (error) {
  console.error(error);
}
const url = 'https://api.anyapi.ai/v1/chat/completions'; const options = { method: 'POST', headers: {Authorization: 'Bearer AnyAPI_API_KEY', 'Content-Type': 'application/json'}, body: '{"stream":false,"tool_choice":"auto","logprobs":false,"model":"devstral-small-2505","messages":[{"role":"user","content":"Hello"}]}' }; try { const response = await fetch(url, options); const data = await response.json(); console.log(data); } catch (error) { console.error(error); }
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Copy
Code is copied
curl --request POST \
  --url https://api.anyapi.ai/v1/chat/completions \
  --header 'Authorization: Bearer AnyAPI_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
  "stream": false,
  "tool_choice": "auto",
  "logprobs": false,
  "model": "devstral-small-2505",
  "messages": [
    {
      "role": "user",
      "content": "Hello"
    }
  ]
}'
curl --request POST \ --url https://api.anyapi.ai/v1/chat/completions \ --header 'Authorization: Bearer AnyAPI_API_KEY' \ --header 'Content-Type: application/json' \ --data '{ "stream": false, "tool_choice": "auto", "logprobs": false, "model": "devstral-small-2505", "messages": [ { "role": "user", "content": "Hello" } ] }'
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Code is copied
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Code examples coming soon...

FAQs

Answers to common questions about integrating and using this AI model via AnyAPI.ai

What is Devstral Small 2505 used for?

Devstral Small 2505 is renowned for its applications in real-time chatbot development, code generation, document summarization, workflow automation, and enhanced knowledge base search functionalities.

How is it different from GPT-4?

Unlike GPT-4, which focuses on high-end resource utilization, Devstral Small 2505 is optimized for lower latency and greater scalability, making it more cost-effective for real-time applications.

Can I access Devstral Small 2505 without a Mistral account?

Yes, via AnyAPI.ai, you can access this model without a separate Mistral account, ensuring ease of integration with any existing systems.

Is Devstral Small 2505 good for coding?

Absolutely. It excels in generating, reviewing, and automating coding processes across multiple programming frameworks.

Does Devstral Small 2505 support multiple languages?

Yes, it supports a wide range of languages, catering to global markets and facilitating widespread usage.

Still have questions?

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