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MiMo-V2.5-Pro

MiMo-V2.5-Pro is Xiaomi’s flagship open-weight trillion-parameter omnimodal MoE language model optimized for long-context, tool-using AI agents.

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What is MiMo-V2.5-Pro?

MiMo-V2.5-Pro is Xiaomi’s ~1T-parameter (42B active) open-weight omnimodal Mixture-of-Experts language model with a 1M-token context window, designed to power advanced AI agents. It is mainly used for complex software engineering and autonomous coding workflows, where it can run hours-long sessions involving code generation, debugging, and project management. It is also used for general-purpose agentic tasks such as tool use, long-horizon planning, and multi-step reasoning over very long documents and contexts. MiMo-V2.5-Pro belongs to Xiaomi’s MiMo-V2.5 family of models, following earlier MiMo-V2 variants and extending them with larger scale, longer context, and improved agent performance.

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).

Provider Input Output Cache read /M Latency Throughput Uptime
Novita $0.52 $1.04 $0.00 — — —
Xiaomi $0.44 $0.87 $0.00 ~150ms ~40 tps ~99.9%

Try this model

Test MiMo-V2.5-Pro right here — free to start.

MiMo-V2.5-Pro
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call the model through the OpenAI-compatible API.

python 
                                        from openai import OpenAI
                                            
                                            client = OpenAI(
                                                api_key="YOUR_API_KEY",
                                                base_url="https://inference.example.com/v1"
                                            )
                                            
                                            response = client.chat.completions.create(
                                                model="xiaomi/mimo-v2-5-pro",
                                                messages=[
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ],
                                            )
                                            
                                            print(response.to_json())
                                        
                                    
                                        {
                                                "model": "xiaomi/mimo-v2-5-pro",
                                                "messages": [
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ]
                                            }

5 Core Capabilities

  • Advanced Text Generation

    Generates coherent, context-aware text for complex tasks with one-million-token context and large 128K-token outputs for long documents.

  • Deep Reasoning

    Optimized Mixture-of-Experts reasoning for complex, multi-step planning, long-horizon tasks, and sophisticated agent workflows and automation.

  • Agent Tool Calling

    Supports function and tool calling for structured outputs, enabling robust AI agents that interact with external systems and APIs.

  • Search-Augmented Answers

    Integrates web search during inference to retrieve up-to-date information, improving factual accuracy and grounding of generated responses.

  • Multilingual Support

    Handles multiple languages for generation and understanding, suitable for global users across diverse linguistic environments and content.

6 Most Valuable Use Cases

  • Agentic workflows automation
  • Complex software engineering
  • Long-horizon task planning
  • Tool-using chat agents
  • Large document analysis
  • Cost-efficient AI deployment

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent Model Routing

    Automatically route each request to the best model across providers based on task, latency, and reliability—no client changes or custom glue code required.

    One endpoint, every model.

  • Cost-Aware Optimization

    Continuously pick the most cost-effective models and configurations for each call, reducing AI spend without sacrificing quality or performance at scale.

    Cut costs, not quality.

  • Automatic Failover

    When a provider degrades or fails, requests transparently fail over to healthy models, keeping your AI features online without on-call fire drills.

    Resilience by default.

  • End-to-End Observability

    Trace every request across models and providers with metrics, logs, and structured events, so you can debug, tune, and prove reliability in production.

    See every token flow.

  • Task-Level Abstractions

    Call high-level tasks like chat, generate, extract, or rank instead of vendor-specific APIs, so your business logic is decoupled from underlying model churn.

    Code to tasks, not vendors.

  • High-Throughput Batch

    Run massive offline or async workloads through a single batch pipeline with retries, chunking, and parallelization handled for you by the platform.

    Ship millions of calls.

When to Use — When NOT to Use

Use it if...

  • You need an on-device assistant optimized for Xiaomi phones and IoT hardware.
  • Your use case involves integrating AI features tightly with Xiaomi system apps and services.
  • You need decent multimodal understanding of photos and screenshots from Xiaomi devices.
  • Your use case involves Chinese-language queries and Xiaomi ecosystem–specific knowledge or content.
  • You need a vendor-supported model aligned with Xiaomi’s privacy and data-handling policies.
  • Your use case involves AI features preinstalled on Xiaomi phones without complex external infrastructure.
  • You need voice or camera–driven assistance tuned for Xiaomi hardware capabilities and sensors.

Avoid if...

  • You need state-of-the-art reasoning performance comparable to top-tier frontier foundation models.
  • Your workload requires broad third-party ecosystem support, tooling, and community integrations.
  • You need guaranteed cross-vendor portability across diverse cloud platforms and non-Xiaomi devices.
  • Your workload requires extensively documented APIs, SDKs, and English-first developer resources.
  • You need transparent, independently benchmarked performance for regulated or safety-critical applications.
  • Your workload requires fine-tuning hooks and flexible model customization exposed to external developers.
  • You need mature enterprise features like granular governance, auditing, and standardized compliance reports.

Frequently Asked Questions

  • What is MiMo-V2.5-Pro?

    MiMo-V2.5-Pro is a Xiaomi large language model available through LLM.API, optimized for general-purpose text generation and assistant-style interactions.

  • What is MiMo-V2.5-Pro best suited for?

    MiMo-V2.5-Pro is best for multi-turn assistants, code generation, and structured data extraction where reliable text understanding and generation are required.

  • What is the context window of MiMo-V2.5-Pro?

    MiMo-V2.5-Pro supports a 16K-token context window, allowing relatively long conversations and documents within a single request.

  • What modalities does MiMo-V2.5-Pro support?

    MiMo-V2.5-Pro supports text-in, text-out interactions only; it does not natively process images, audio, or video.

  • How is MiMo-V2.5-Pro priced on LLM.API?

    LLM.API bills MiMo-V2.5-Pro per 1,000 tokens of input and output, with exact rates listed on the LLM.API pricing page.

  • What latency can I expect from MiMo-V2.5-Pro on LLM.API?

    Typical end-to-end latency is around 500–1500 ms for short prompts, depending on request size, region, and current load.

  • How do I call MiMo-V2.5-Pro through the LLM.API?

    Specify provider "Xiaomi" and model "MiMo-V2.5-Pro" in your LLM.API request along with your API key and usual completion parameters.

  • How does MiMo-V2.5-Pro compare to similar Xiaomi models?

    MiMo-V2.5-Pro offers stronger reasoning and coding capabilities than earlier MiMo versions, at slightly higher cost and similar latency.

  • What limitations does MiMo-V2.5-Pro have?

    MiMo-V2.5-Pro may hallucinate facts, lacks real-time internet access, and should not be used as the sole source for high-stakes decisions.

  • Can I use MiMo-V2.5-Pro for streaming responses?

    Yes, MiMo-V2.5-Pro supports token streaming via LLM.API when you enable streaming in the request options.

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