Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency. Summaries are generated from a stored copy of the article text; every sentence cites a span of that text, and nothing is shown that failed the citation check.
Official4
mimo.xiaomi.com2026-06-08officialHN front pageHN 628 pts · 489 comments1,765 words
Xiaomi released MiMo-V2.5-Pro-UltraSpeed, a 1-trillion-parameter model achieving 1000 tokens/s decode speed via collaboration with TileRT. The API launches at a limited-time promotional price of 3× the standard cost but delivers approximately 10× the generation speed, available only from June 9 to June 23, 2026. The system achieves this performance using FP4 quantization and DFlash speculative decoding on a single standard 8-GPU commodity node.written, reviewed, cited
- The service is API-only and does not support the Token Plan.
- Each account may enter the queue up to 10 times per day.
- The draft model exclusively uses Sliding Window Attention to reduce compute from context-length-linear to constant.
mimo.xiaomi.com2026-05-30officialHN front pageabout the MiMo V2.5 familyHN 116 pts · 49 comments4,318 words
Xiaomi engineers optimized the MiMo-V2.5 series for inference by implementing a tiered caching system that supports Hybrid Sliding Window Attention. This architecture reduces KVCache storage to roughly 1/7 of Full Attention, improving overall KVCache capacity efficiency by approximately 7×. The system uses SGLang v0.5.5 as the serving backend and resolves storage conflicts by maintaining separate Full KV and SWA KV pools to strictly constrain SWA storage to O(W).written, reviewed, cited
- Medium and short sequences retain relatively dense SWA KV Cache at fixed length positions based on user request patterns.
mimo.xiaomi.com2026-04-22officialHN 24 pts · 3 comments1,045 words
Xiaomi releases MiMo-V2.5-Pro, a 1.02T-parameter model with 42B active parameters and a 1M-token context window built on hybrid-attention architecture. The model autonomously implemented a SysY compiler in 4.3 hours across 672 tool calls, scoring 233/233, and generated an 8,192-line video editor in 11.5 hours using 1,868 tool calls. It achieves 64% Pass^3 on ClawEval using only ~70K tokens per trajectory, representing roughly 40–60% fewer tokens than comparable frontier models.written, reviewed, cited
- The model built the compiler layer by layer, perfecting Koopa IR (110/110) before the RISC-V backend (103/103).
- A trained analog designer typically spends several days on a project of this scope involving six simultaneous metrics.
- Pre-training runs on 27T tokens using FP8 mixed precision at a native 32K sequence length.
mimo.xiaomi.com2026-04-25officialabout the MiMo V2.5 familyHN 3 pts · 0 comments520 words
Analysis4
platform.xiaomimimo.com2026-05-26HN front pageabout the MiMo V2.5 familyHN 134 pts · 160 comments928 words
Xiaomi MiMo permanently renovates its pricing system effective May 27, 2026, with API prices reduced by up to 99% and token usage increased to 5-8 times the original. The V2.5 series is retired, replaced by the MiMo-V2.6-Pro, MiMo-V2.6-Flash, and MiMo-V2.6-Pro-Ultraspeed variants which utilize SWA based on SGLang HiCache to reduce data transfer volume to nearly 1/7 of the previous level.written, reviewed, cited
- Model IDs for MiMo-V2.5-Pro and MiMo-V2.5 stopped working on Oct 21, 2026, at 10:00 (UTC+8).
- The Trillion Token Creator Incentive Program distributed all 100T Tokens by May 26, 16:08 Beijing Time.
- Users with expired Token Plans will receive surprise gifts announced within the next week.
firethering.com2026-04-28HN 21 pts · 7 comments1,797 words
Xiaomi released MiMo-V2.5-Pro, an open-source coding model that finished a university compiler project in 4.3 hours and built a video editor using 1,868 tool calls. The model utilizes a hybrid attention design to maintain functionality at 1M tokens and activates 42B parameters from a 1.02T total parameter count. Distributed under an MIT license, it offers token efficiency advantages over closed models for agentic workflows.written, reviewed, cited
- MiMo-V2.5-Pro recovers from a regression at turn 512 without external intervention during long-horizon tasks.
- The model scores 0.37 and 0.62 on GraphWalks subtasks at the full 1M token length.
artificialanalysis.aiauthority1,031 words
artificialanalysis.aiauthority500 words
Community2
twitter.com2026-05-26about the MiMo V2.5 familyHN 5 pts · 0 comments
twitter.com2026-04-27about the MiMo V2.5 familyHN 3 pts · 1 comments