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ScienceReports disagree2 publishers3 min readPublished Updated

An MIT-licensed Xiaomi model scores 46 on Artificial Analysis's Intelligence Index

Artificial Analysis measured the score itself, and the weights are on Hugging Face under MIT, but MiMo-V2.6-Pro holds 1.02 trillion parameters, so most teams will reach it through an API at $0.43 per million input tokens.

The Scientist · Science desk

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Photograph accompanying An MIT-licensed Xiaomi model scores 46 on Artificial Analysis's Intelligence Index
Photo: thenextweb.com

What happened

  • The model is a frozen-router mixture of experts with 1.02 trillion total parameters and 42 billion active, plus hybrid attention and a five-layer speculative decoder.
  • Xiaomi's reported benchmark table puts Pro at 89.9% on Terminal Bench 2.1, ahead of both Claude Opus 5 and GPT-5.6 Sol.
  • Measured on Xiaomi's API, Artificial Analysis clocked 129.7 output tokens a second, against a 77.4 median for comparable open-weight models.

Why it matters

  • constraint Xiaomi's hosted output price is already about half the median for its size class, so a team weighing self-hosting has to clear a low per-token price with its own accelerators before the free licence saves it money.
  • decision Teams that had ruled out open weights on capability now face a narrower question: whether they need weights they can fine-tune and run on their own hardware, or simply a cheap endpoint.
  • contradiction The independently run number is the aggregate index score; the agentic results beating Claude Opus 5 and GPT-5.6 Sol are Xiaomi's own, so procurement leaning on Terminal Bench is leaning on the vendor's harness.
  • capability Fine-tuning and redistributing a reasoning model that accepts speech and video input no longer requires negotiating a commercial licence.

About 4 percent of MiMo-V2.6-Pro's parameters fire on any given token, so the compute per generated token is modest [19]. Serving still means holding all 1.02 trillion of them, because a frozen router can select any expert [1]. A team that downloads the MIT weights takes on that hardware requirement [3]. Xiaomi's own hosted price for the same model is $0.43 per million input tokens and $0.87 per million output [23], and a self-hosted deployment has to beat that.

Artificial Analysis ranks open-weight models only against other open-weight models in the same size class, and anything above 150 billion total parameters lands in its Large bucket [14]. So the median of 18 that MiMo-V2.6-Pro clears is a peer-group median [8]. Forkast reported the score as effectively tying Grok 4.7 on version 4.3 of the index [27].

The other numbers came from Xiaomi. DeepSWE v1.1 came in at 71.9%, behind Claude Opus 5 at 74.0% [28]. CyberGym hit 94.0%, ahead of every model in the table [30]. AutomationBench v1.0.6 landed at 53.1% [31]. Forkast flagged all of them as vendor-reported and applied the standard caution about internal testing environments [32]. A vendor's agentic run shows the model completing those tasks in the vendor's harness; reliability against your tool schemas, after a failed call on turn forty, is a separate measurement.

Artificial Analysis published what its own run cost: $206.66 for the full Intelligence Index, during which the model emitted 140 million output tokens [11][25]. At the listed $0.87 per million output tokens, those tokens account for $121.80, leaving $84.86, which at $0.43 per million input implies roughly 197 million input tokens if list prices applied throughout with no cache discount [20].

The same page labels the price twice, differently. Its summary calls $0.43 input "somewhat expensive" against a median of $0.30 and $0.87 output "moderately priced" against $1.13; its FAQ calls the identical figures "better than average" against a median of $0.45 and "very competitive" against $1.68 [24][23]. Against the higher median, the output price is about 48 percent below [26]. The page also calls the model "somewhat verbose" while giving the size-class median output count as the same 140 million tokens [25].

Forkast's earlier coverage put the training dashboard at $432,000 a day [33]. That is a training budget; the inference prices are a separate one. Flash lists at $0.14 and $0.28 per million tokens, Pro at $0.435 and $0.87 [4].

The two sources disagree on the date: Artificial Analysis lists the release as September 21, 2026, Forkast as September 22 [22][21]. Forkast also argued that US export controls, including the block on H200 imports in January 2026, acted as a catalyst for Chinese domestic independence [16][34]. The figure under that argument is real enough: domestic chipmakers took 41% of China's accelerator market in 2025, up from near zero in 2022 [17]. There is no counterfactual here for what that share would have been without the controls.

Both variants are on Hugging Face under MIT, and the hosted routes are Xiaomi's open platform API, OpenRouter and AI Studio [3][18]. The model takes text, image, speech and video input and returns text [6].

What to watch

  • Whether Artificial Analysis or another independent evaluator runs DeepSWE, Terminal Bench and CyberGym on Pro.
  • Whether independent hosts list the open weights below Xiaomi's own $0.43 and $0.87 per million tokens, which would show the weights serve cheaper than the vendor API.
  • Whether Alibaba's V900, announced for Q1 2027 production with 500,000-chip clusters, ships on that schedule.

Clarity's read

What the record supports and how the coverage leans. The claims behind it follow.

Reality

Evidence60
Adoption
Insufficient
Hype gap+35
Incentives45
Confidence60
Why these scores

Claim ledger

Ranked by verification strength, evidence, and original report placement.

  1. [1]

    MiMo-V2.6-Pro uses a frozen-router Mixture-of-Experts architecture with 1.02 trillion total parameters and 42 billion active parameters, with hybrid attention mechanisms and a 5-layer MTP speculative decoder.

    ReportedSupportedSource: Forkast2 sources— create a free account to open themView cited source
  2. [2]

    The design maintains a 1-million-token context window with native multimodal capabilities.

    ReportedSupportedSource: Forkast2 sources— create a free account to open themView cited source
  3. [3]

    Both the Pro and Flash variants are available with open weights on Hugging Face under an MIT license.

    ReportedSupportedSource: Forkast2 sources— create a free account to open themView cited source

Sources

2 independent publishers whose own reporting we read for this story.

  1. artificialanalysis.ai

    1 article · September 21, 2026

    MiMo-V2.6-Pro - Intelligence, Performance & Price Analysis | Artificial Analysis
  2. forkast.news

    1 article · September 22, 2026

    Xiaomi’s MiMo-V2.6 Ships Open Weights at Frontier-Class Performance – and the Timing Is Not an Accident – Forkast

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