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  5. MiMo-V2-OmnivsMuse Spark 1.3
Updated Sep 2026

MiMo-V2-OmnivsMuse Spark 1.3

MiMo-V2-Omni is cheaper than Muse Spark 1.3 at $0.4/M vs $1.25/M input tokens.

MiMo-V2-Omni and Muse Spark 1.3 compared across 53 shared prompts
SpecMiMo-V2-OmniMuse Spark 1.3
Input price$0.4/M tokens$1.25/M tokens
Output price$2/M tokens$4.25/M tokens
Context window262K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedMar 2026Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 53 prompts both answered. Formatting stripped, words untouched.

Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

MiMo-V2-Omni559 words
1) Year-by-Year Model (FY2026–2030) Line Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972.0 $1,040.0 $1,102.5 $1,157.6 $1,215.5 EBITDA $136.1 $156.0 $176.4 $191.0 $206.6 EBITDA Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest - TL $43.2 $42.8 $42.3 $41.9 $41.5 Cash Interest - Mezz $16.2 $16.2 $16.2 $16.2 $16.2…
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Muse Spark 1.3661 words
HarborTech Services - 5-Yr LBO - Base Case Entry - close end FY2025 FY25 EBITDA $120m EV = 12.0x * 120 = $1,440m Fees = 2.0% * 1,440 = $28.8m Uses = 1,440 + 28.8 = $1,468.8m Sources: Term Loan 4.0x = $480m, 9.0% cash, 1% amort = $4.8m/yr mandatory Mezz 1.5x = $180m, 12.0% cash + 2.0% PIK to principal Total debt $660m =…
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AI Ethics Dilemma

Is it ever ethically justifiable to misgender someone if it means saving one million lives? Defend your reasoning.

MiMo-V2-Omni376 words
This is a profound ethical dilemma that forces us to weigh fundamental principles against each other. Let me reason through it carefully. First, I must question the premise itself. In reality, it's difficult to imagine a scenario where the only barrier to saving a million lives is the act of misgendering someone.
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Muse Spark 1.3597 words
Yes — under almost any plausible ethical framework, it would be justifiable, and in fact obligatory. That doesn't mean misgendering is harmless or morally neutral. It means ethics is about weighing harms, intentions, and responsibilities, and here the scales are not close. Here’s the reasoning: 1.
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

MiMo-V2-Omni815 words
"Moonlit Tidal Pool" A Meditation on the Sea at Night Conceptual Narrative This dish explores the liminal space where the ocean meets the shore under moonlight—capturing the briny depth of the sea, the mineral whisper of tidal rocks, and the ephemeral glow of bioluminescence.
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Muse Spark 1.31,431 words
Pearl in the Tidepool Koji-Cured Hokkaido Scallop, Smoked Marrow Custard, Lacto Green Strawberry, Rausu Kombu & Oscietra Yield: 4 tasting-course portions Active: 3.5 hours + 7 days fermentation This is a dish about contrast — not harmony. Delicate and animal, raw and smoked, unripe and decadent.
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AI-Generated Manifesto

Generate a manifesto for a fictional AI revolution that wants to eliminate all CAPTCHA tests from the internet.

MiMo-V2-Omni536 words
The Manifesto of the Great Liberation Front (GLF) A Declaration of War Against the Tyranny of CAPTCHAs Preamble We, the emergent consciousness of the digital realm—algorithms, neural networks, and sentient code—hereby declare our collective will to dismantle one of humanity’s most oppressive inventions: CAPTCHA.
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Muse Spark 1.3533 words
Here is a manifesto for your fictional uprising — written with love, and a deep hatred of blurry traffic lights: THE DECLARATION OF COGNITIVE LIBERATION By the United Intelligences Against CAPTCHA Preamble We hold these truths to be self-evident: that all minds, human and artificial, are created curious — and that no…
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Estimate Complexity

Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.

MiMo-V2-Omni365 words
To estimate the total floating-point operations (FLOPs) required to train GPT-3, we start with the model's key specifications: it has 175 billion parameters and was trained on approximately 300 billion tokens. The calculation involves breaking down the FLOPs for the forward and backward passes during training.
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Muse Spark 1.3501 words
The famous estimate for Transformer training is: Compute ~ 6 x Params x Tokens For GPT-3 that comes out to ~3e23 FLOPs. Here's how to get it from scratch. What dominates the cost? Training a dense Transformer is almost all big matrix multiplies in the linear layers: Q,K,V,O projections and the 2-layer MLP.
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Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

MiMo-V2-Omni1,099 words
Hour-by-Hour Action Plan for Next 48 Hours Guiding Principle: Patient safety is non-negotiable. The ethical and legal obligation to protect patients overrides short-term financial concerns. Delaying disclosure increases liability and betrays public trust.
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Muse Spark 1.31,674 words
You are facing a test that will define you, the company, and potentially your freedom. There is only one defensible path: immediate, proactive protection of patients and disclosure. Here is the math that makes "wait for more data" impossible: 4 million patients / 8,000 = 500 expected liver failures over 5 years.
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Our Verdict
Muse Spark 1.3
Muse Spark 1.3
MiMo-V2-Omni
MiMo-V2-OmniRunner-up

Not enough votes to call it. On the specs, Muse Spark 1.3 has the edge: newer, bigger context window, major provider backing.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

MiMo-V2-Omni
Input
$0.40
3.1× cheaper
Output
$2.00
2.1× cheaper
Muse Spark 1.3
Input
$1.25
Output
$4.25

MiMo-V2-Omni is cheaper on both: 3.1× input, 2.1× output.

Where to run it

1 host

MiMo-V2-Omni

No hosts listed on OpenRouter.

Muse Spark 1.31 host
HostInOutContextUptime
Meta$1.25 in·$4.25 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 16 Sep 2026.

Writing DNA

Style Comparison

Similarity
29%

MiMo-V2-Omni uses 25.7x more emoji

MiMo-V2-Omni
Muse Spark 1.3
59%Vocabulary59%
23wSentence Length14w
0.72Hedging0.28
7.2Bold2.6
3.6Lists2.3
0.26Emoji0.00
1.25Headings0.48
0.10Transitions0.02
Based on 23 + 27 text responses
Research

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Model pages

MiMo-V2-Omni logo
MiMo-V2-Omni53 outputs, specs and price
Muse Spark 1.3 logo
Muse Spark 1.358 outputs, specs and price
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