MiMo-V2-Pro

mimo-v2-pro

MiMo-V2-Pro is Xiaomi's flagship foundation model with over 1T parameters and a 1M-token context window, optimized for advanced agentic workflows. It is highly adaptable to general agent frameworks such as OpenClaw, delivering strong performance in complex, real-world task execution. Ranking among the top tier on benchmarks like PinchBench and ClawBench, with performance approaching models like Opus 4.6, MiMo-V2-Pro is designed to act as the core intelligence of agent systems, orchestrating workflows, driving production engineering tasks, and delivering reliable results at scale.

Context: 1.0M tokens
Endpoint

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Pricing

Input$1.00 / 1M

Output$3.00 / 1M

Cache Write (5m)$1.00 / 1M

Cache Write (1h)$1.00 / 1M

Cache Read$1.00 / 1M

Web Search$0 / 1M

Quick Start

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Endpoint

python

from openai import OpenAI client = OpenAI(    api_key="YOUR_API_KEY",    base_url="https://api.apertis.ai/v1") response = client.chat.completions.create(    model="mimo-v2-pro",    messages=[        {"role": "user", "content": "Hello!"}    ],    max_tokens=1024,    temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(#     model="mimo-v2-pro",#     messages=[{"role": "user", "content": "Hello!"}],#     extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )

Supported Parameters

API docs

Common7 params

modelmessagesmax_tokenstemperaturetop_pstreamtools

Extended4 params

reasoning_effortstream_optionsthinkingextra_body

Cursor IDE Model IDs

Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.

mimo-v2-pro

Compare with Other Models

See how this model compares to others from the same provider.

MiMo-V2.5-Pro

MiMo-V2.5-Pro is Xiaomi's flagship model, delivering top-tier performance in agentic capabilities, complex software engineering, and long-horizon tasks. It ranks highly on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro, demonstrating strong real-world reliability. The model can autonomously complete professional tasks that would take human experts days or weeks, executing thousands of tool calls within a single workflow. With a 1M-token context window, it is well suited for integration into advanced agent frameworks and large-scale task orchestration systems.

Context: 1.0M
Input: $1.00/M
Output: $3.00/M

MiMo-V2-Flash

MiMo-V2-Flash is an open-source Mixture-of-Experts (MoE) foundation model developed by Xiaomi, featuring 309B total parameters with 15B activated per token and a hybrid attention architecture. It supports a 256K context window and a hybrid thinking mode toggle, enabling flexible trade-offs between speed and reasoning depth. The model excels in reasoning, coding, and agentic workflows, ranking #1 globally among open-source models on benchmarks such as SWE-bench Verified and SWE-bench Multilingual. With performance comparable to leading proprietary models like Claude Sonnet 4.5 at a fraction of the cost, MiMo-V2-Flash is well suited for efficient, high-performance deployments.

Context: 262.1K
Input: $0.09/M
Output: $0.29/M

MiMo-V2-Omni

MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video, and audio inputs within a unified architecture. It combines strong multimodal perception with advanced agentic capabilities, including visual grounding, multi-step planning, tool use, and code execution. With a 256K context window, MiMo-V2-Omni is well suited for complex real-world tasks that span multiple modalities, enabling integrated reasoning and execution across diverse input types.

Context: 262.1K
Input: $0.40/M
Output: $2.00/M

MiMo-V2.5

MiMo-V2.5 is Xiaomi's native omnimodal model, delivering pro-level agentic performance at roughly half the inference cost. It surpasses MiMo-V2-Omni in multimodal perception, particularly in image and video understanding. With a 1M-token context window, it can handle complete documents, extended conversations, and complex task contexts in a single pass. Combining strong reasoning, rich perception, and cost efficiency, MiMo-V2.5 is well suited for integration into advanced agent frameworks and real-world multimodal applications.

Context: 1.0M
Input: $0.40/M
Output: $2.00/M