Xiaomi’s MiMo V2.5 Pro has landed at 54 in the Artificial Analysis Intelligence Index, tied with Moonshot’s Kimi K2.6 - the current top open weights model. MiMo V2.5 Pro’s weights are expected to be released soon, which would make MiMo V2.5 Pro the first equal open weights model - slightly ahead of DeepSeek V4 Pro

@Xiaomi’s MiMo V2.5 Pro shows an impressive improvement over MiMo V2 Pro (49), the previous generation of Xiaomi's flagship model family, which was released just over a month ago on March 19, 2026.

Key takeaways:

➤ MiMo V2.5 Pro is on the pareto frontier of our Intelligence Index vs Cost to Run Intelligence Index chart. It was slightly cheaper to run than GLM-5.1, and slightly more intelligent. It was significantly cheaper to run than Kimi K2.6, driven by using just over half the number of output tokens.

➤ MiMo V2.5 Pro will be the leading open weights model in GDPval-AA, our agentic real-world work tasks benchmark. It scores 1578, ahead of DeepSeek V4 Pro (1554), GLM-5.1 (1535), MiniMax-M2.7 (1514), and Kimi K2.6 (1484).

➤ It makes progress in reasoning and instruction following. The model scores 34% on HLE (+6% from MiMo V2.0) and 80% on IFBench (+11% from MiMo V2.0). However, compared to the previous generation, there is a small regression in CritPt (5% to 4%).

➤ MiMo V2.5 Pro's token efficiency remains competitive against peers in a similar intelligence tier, using ~92M output tokens for the Intelligence Index. This is more efficient than Kimi K2.6 (~170M) and GLM 5.1 (~110M). However, it does use 19% more than the previous generation model, MiMo V2 Pro (77M).

➤ Priced at $1.00/$3.00 per million input/output tokens on Xiaomi’s first-party API, MiMo V2.5 Pro is relatively cost-efficient for its intelligence tier. It costs only $462 to run the Artificial Analysis Intelligence Index, compared to $948 for Kimi K2.6 and $544 for GLM 5.1.

➤ MiMo V2.5 Pro scores 4 on the AA-Omniscience Index, a proprietary Artificial Analysis evaluation that measures factual accuracy and hallucination. This is a slight regression from MiMo V2 Pro (5), though both models still trail proprietary frontier models. MiMo V2.5 Pro demonstrates a relatively low hallucination rate (25%) but also low accuracy (23%).

Additional model details:

➤ Context window: 1M tokens ➤ Parameters: 1T total, 42B active ➤ License: Xiaomi has publicly announced that weights are to be released soon. The model will show on Artificial Analysis as a ‘proprietary’ until the weights are released ➤ Release date: April 22, 2026 ➤ Availability: MiMo V2.5 Pro is available via Xiaomi's first-party API