Models › MiMo family

XiaomiMiMo MIT out 18 months ago

7.83B parameters, text in, text out, 32K tokens of context.

Verified 2026-10-25 Rank #698 in LLMs · score 72.1 method v1 Sources 3 Downloads 30d 31k · #421 of 619 tracked

Can I run it?4.7GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?MITPermissivelicence file2026-10-24
Do people use it?31kdownloads, 30 days#421 of 619 we track · below the median+0 likes, downloads −1% this week280 likesHugging Face2026-10-24

Worth reading

Picked by rule from 11 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 482 HN pts
github.com 2025-04-30 482 HN pts · 193 comments 1.4k words about the MiMo family family
Latest · 33 days ago

MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis

MiMo-V2.6-Pro is a multimodal open-weight model from Xiaomi released on September 21, 2026, that scores 46 on the Artificial Analysis Intelligence Index.

  • The model uses a 7:2:1 cache hit/input/output ratio to calculate a blended rate of $0.18 per 1M tokens.
  • The model generates 140M output tokens on the Intelligence Index, which is described as somewhat higher than average.
artificialanalysis.ai 2026-09-22 166 HN pts · 68 comments 973 words about the MiMo family family

11 best of 11 tracked

The 2 picks above, plus these 9. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. ArticleMiMo-v2.5-Pro-UltraSpeed: 1T model with 1000 tokens per secondmimo.xiaomi.com · 2026-06-08 · 628 HN pts · official
  2. ArticleMiMo Code is now released and open-sourcemimo.xiaomi.com · 2026-06-11 · 557 HN pts · official
  3. ArticleInference Optimization for MiMo v2.5: Pushing Hybrid SWA Efficiency to the Limitmimo.xiaomi.com · 2026-07-07 · 116 HN pts · official
  4. ArticleXiaomi MiMo-v2.5 Series API Permanent Price Reduction Up to 99%platform.xiaomimimo.com · 2026-05-26 · 134 HN pts
  5. ArticleXiaomi MiMo Token Plan is Now Globally Availableplatform.xiaomimimo.com · 2026-05-26 · 79 HN pts
  6. ArticleXiaomi releases MiMo-v2.5 Family weights with strong coding and agent benchmarksfirethering.com · 2026-04-28 · 21 HN pts
  7. ArticleWorld's First Fully Programmable and Open-Source Massive-MIMO Platformrenew-wireless.org · 2020-08-02 · 87 HN pts
  8. DiscussionXiaomi Mimo-v2.5 pricing is now permanently reducedtwitter.com · 2026-05-26 · 5 HN pts
  9. ArticleMiMo-V2-Pro LLM nearing GPT-5.2, Opus 4.6 performance at a fraction of the costventurebeat.com · 2026-03-19

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

No API provider serves it, so its downloads are people running it themselves: 3 quantized builds and 8 Spaces.

  • As a service0no API provider listed
  • On own hardware3quantized builds
  • Built on00 fine-tunes · 0 adapters · 0 merges
  • In apps8Hugging Face Spaces

Top Spaces running it: ISEEKYAN/megatron_memory_estimator ♥ 35 · ISEEKYAN/megatron_memory_estimator_old ♥ 19 · orangewong/xiaomi-mimo-7b-rl ♥ 8

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Fits a 16 GB card at INT4

About 4.7 GB at INT4, 9.4 GB at FP8, 19 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 4.7 GB of weights (estimate; KV cache and activations extra)INT44.7 GBFP8: about 9.4 GB of weights (estimate; KV cache and activations extra)FP89.4 GBBF16: about 19 GB of weights (estimate; KV cache and activations extra)BF1619 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 4.7 GB of weights (estimate; KV cache and activations extra)INT44.7 GBFP8: about 9.4 GB of weights (estimate; KV cache and activations extra)FP89.4 GBBF16: about 19 GB of weights (estimate; KV cache and activations extra)BF1619 GB

Estimate params × bytes per param × 1.2 · how we estimate

The story so far

Weights, every dated article, and repo commits on one rail.

10 dated articles and 10 repo commits so far

Teal is the weights (2025-04-29), amber triangles are 10 dated articles (each links to it), grey ticks are repo commits.

What people built on it

3 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

3 derivatives on the Hub, most of them quantized

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

3 quantized (Hugging Face model tree)3 quantized
3 quantized (Hugging Face model tree)3 quantized

All variants →

Reference

Everything else, folded: the full tables, every source.

What the card says

1 cited sentence

Summary generated, cited

The model is designed for reasoning tasks and is released under an MIT license.[1][2]

  1. “born for reasoning tasks”
  2. license

Generated 2026-10-07 15:13 UTC by parasail-gemma-4-26b-a4b-it; each numeral points at the fact it rests on. Not a verdict.

Use-case evidence

4 use cases

What it is good at 4 use cases

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

20 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesMiMoForCausalLM
Model typemimo
Dtypebfloat16
Params by dtypeBF16: 7,833,409,536
Size bandM
MoEno
Context length32,768 (config.json max_position_embeddings)
PapersarXiv:2505.07608
LicenseMIT (mit)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · MiMoForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · MiMoForCausalLM · 773cb938fe9484a8f7e7e46fb1b1fe96412c59ed

vLLM registry (7050ef881ff0835f6890a47db1859a24c65481d6) · SGLang registry (773cb938fe9484a8f7e7e46fb1b1fe96412c59ed) · Matched by architecture class name against each project's registry on main; 'supported' means the architecture is registered, not that this checkpoint was tested.

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for MiMo-7B-RL: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)19 GB · Single GPU (<24 GB)
FP8 (1 byte/param)9.4 GB · Single GPU (<24 GB)
INT4 (0.5 bytes/param)4.7 GB · Single GPU (<24 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

All variants

3 variants

Lineage

Original model Family: XiaomiMiMo/MiMo 3 derivatives on the Hub

quantized: 3

Top variants (3 shown, ranked by downloads)

Quant
3 rows
Variant Relation Quant Params Band License Author Likes Downloads
jedisct1/MiMo-7B-RL-GGUF quantized GGUF — — mit jedisct1 30 43.4k
quantflex/MiMo-7B-RL-nomtp-GGUF quantized GGUF — — mit quantflex 2 6.6k
mlx-community/MiMo-7B-RL-4bit quantized -4bit 7.62B M mit mlx-community 1 1.5k

Repository changelog

10 commits

Repository changelog 10 commits

DateCommitSHA
2025-06-05 Update README.md 6299b5a
2025-05-13 Update README.md 8aa36ea
2025-05-13 [Add] `tokenizer_class` in config to make it usable by the `pipeline` API (#10) 5304ef1
2025-05-05 Add library_name to the model (#2) 5d40cdb
2025-05-05 Update README.md 9c071e0
2025-04-30 Update formulas in README.md 8c8a496
2025-04-30 init Xiaomi-MiMo 163b6d7
2025-04-30 init Xiaomi-MiMo 68c4525
2025-04-29 init Xiaomi-MiMo 6103a58
2025-04-29 initial commit 54501ee

Articles and coverage

11 pieces

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.

Official3

mimo.xiaomi.com2026-06-08officialHN front pageabout the MiMo familyHN 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.com2026-06-11officialHN front pageabout the MiMo familyHN 557 pts · 315 comments39 words
mimo.xiaomi.com2026-07-07officialHN front pageabout the MiMo 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.

Analysis6

artificialanalysis.ai2026-09-22authorityHN front pageabout the MiMo familyHN 166 pts · 68 comments973 words
MiMo-V2.6-Pro is a multimodal open-weight model from Xiaomi released on September 21, 2026, that scores 46 on the Artificial Analysis Intelligence Index. It costs $0.43 per 1M input tokens and $0.87 per 1M output tokens while generating output at 52 tokens per second. The model operates under the MIT license with 1.0 trillion total parameters and 42 billion active parameters during inference.written, reviewed, cited
  • The model uses a 7:2:1 cache hit/input/output ratio to calculate a blended rate of $0.18 per 1M tokens.
  • The model generates 140M output tokens on the Intelligence Index, which is described as somewhat higher than average.
platform.xiaomimimo.com2026-05-26HN front pageabout the MiMo 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.
platform.xiaomimimo.com2026-05-26about the MiMo familyHN 79 pts · 57 comments903 words
firethering.com2026-04-28about the MiMo familyHN 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.
github.com2025-04-30authorityHN front pageabout the MiMo familyHN 482 pts · 193 comments1,416 words
renew-wireless.org2020-08-02about the MiMo familyHN 87 pts · 35 comments

Community1

twitter.com2026-05-26about the MiMo familyHN 5 pts · 0 comments
All coverage tracked for this model (11) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
MiMo-v2.6-Pro: Intelligence, Performance and Price Analysisartificialanalysis.ai2026-09-222026-10-07hn
Inference Optimization for MiMo v2.5: Pushing Hybrid SWA Efficiency to the Limitmimo.xiaomi.com official2026-07-072026-10-07hn
MiMo Code is now released and open-sourcemimo.xiaomi.com official2026-06-112026-10-07hn
MiMo-v2.5-Pro-UltraSpeed: 1T model with 1000 tokens per secondmimo.xiaomi.com official2026-06-082026-10-07hn
Xiaomi MiMo Token Plan is Now Globally Availableplatform.xiaomimimo.com2026-05-262026-10-07hn
Xiaomi MiMo-v2.5 Series API Permanent Price Reduction Up to 99%platform.xiaomimimo.com2026-05-262026-10-07hn
Xiaomi Mimo-v2.5 pricing is now permanently reducedtwitter.com2026-05-262026-10-07hn
Xiaomi releases MiMo-v2.5 Family weights with strong coding and agent benchmarksfirethering.com2026-04-282026-10-07hn
MiMo-V2-Pro LLM nearing GPT-5.2, Opus 4.6 performance at a fraction of the costventurebeat.com2026-03-192026-10-07hn
Xiaomi MiMo Reasoning Modelgithub.com2025-04-302026-10-07hn
World's First Fully Programmable and Open-Source Massive-MIMO Platformrenew-wireless.org2020-08-022026-10-07hn

Papers

1 paper

Papers 1

arXiv links found in the model card and its tags. "Peer-reviewed" is shown only with evidence: a published venue in OpenAlex (measured) or the authors' own journal reference on arXiv (reported).

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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:41 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:13 UTC · Last verified 2026-10-25

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