Xiaomi • LLM
MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro....
Context Window
1.0M tokens
Input Price/1M
$0.43
Output Price/1M
$0.87
Parameters
—
Speed
53 tok/s
Latency (TTFT)
2.1s
Max Output
131K tokens
Xiaomi: MiMo-V2.5-Pro results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 43.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SciCode | 50.0 | 100.0 | — |
| AA Coding Index | 45.5 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 73.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 53.8 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 87.0 | 100.0 | — |
| IFBench | 80.0 | 100.0 | — |
| HLE | 34.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 94.0 | 100.0 | — |
Xiaomi: MiMo-V2.5-Pro is an AI model developed by Xiaomi, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via Xiaomi's cloud API. With a context window of 1.0M tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Xiaomi: MiMo-V2.5-Pro is usage-based, priced at $0.435/1M input tokens and $0.87/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Xiaomi: MiMo-V2.5-Pro was evaluated on 9 different benchmarks, covering categories like Agentic, Coding, Long Context, overall, Reasoning, Tool Use. Results show exceptional performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Xiaomi: MiMo-V2.5-Pro is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), high-volume chatbots and automated support, complex reasoning, math problem solving, and logical analysis, text generation, summarization, translation, and general assistance.
In the 2026 AI model ecosystem, Xiaomi: MiMo-V2.5-Pro competes directly with similarly capable models. Xiaomi competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro....
Xiaomi: MiMo-V2.5-Pro costs $0.435/1M input tokens and $0.87/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, Xiaomi: MiMo-V2.5-Pro scored: Terminal-Bench Hard: 43/100, SciCode: 50/100, AA Coding Index: 45.5/100. See the full table above for a detailed comparison.
No, Xiaomi: MiMo-V2.5-Pro is a proprietary model from Xiaomi. It is available via cloud API. For open source alternatives, check our open source model ranking.
Xiaomi: MiMo-V2.5-Pro excels at complex reasoning and problem solving. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →