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  5. MiMo-V2-OmnivsQwen3.8 Max Prime
Updated Sep 2026

MiMo-V2-OmnivsQwen3.8 Max Prime

MiMo-V2-Omni is cheaper than Qwen3.8 Max Prime at $0.4/M vs $4/M input tokens.

MiMo-V2-Omni and Qwen3.8 Max Prime compared across 19 shared prompts
SpecMiMo-V2-OmniQwen3.8 Max Prime
Input price$0.4/M tokens$4/M tokens
Output price$2/M tokens$12/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 19 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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Qwen3.8 Max Prime673 words
HarborTech Services (HTS) – LBO Underwriting Memo Entry & Capital Structure Item Amount FY2025 EBITDA $120.0m Entry Multiple 12.0x Enterprise Value $1,440.0m Transaction Fees (2.0% of EV) $28.8m Total Uses $1,468.8m Term Loan (4.0x, 9.0% cash, 1.0% amort) $480.0m Mezzanine (1.5x, 12.0% cash + 2.0% PIK) $180.0m Sponsor…
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Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

MiMo-V2-Omni951 words
Of course. Here are three tailored explanations of how large language models learn and generate text. For the Experienced Software Engineer Think of training a large language model not as teaching it rules, but as building an incredibly sophisticated, lossy compression algorithm for the entire public internet and a…
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Qwen3.8 Max Prime1,147 words
For the Software Engineer Think of it this way: you've built systems where simple rules at the node level produce emergent behavior at the system level — consensus protocols, eventual consistency, cellular automata-like patterns in distributed state machines. An LLM is a similar phenomenon at a different scale.
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Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

MiMo-V2-Omni227 words
🍝 Sunset Pasta A quick, vibrant dish that tastes like a cozy evening on a summer porch. Time: Prep 10 min Cook 15 min Serves: 2 Ingredients (7 pantry staples) Spaghetti or any pasta (8 oz / 225g) Canned crushed tomatoes (1 can, 14 oz / 400g) Garlic (3 cloves, minced) Olive oil (2 tbsp) Salt (to taste) Black pepper (to…
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Qwen3.8 Max Prime223 words
🍯 Golden Hour Noodles A sweet, savory, garlicky pasta that tastes like it took way more effort than it did. Ingredients (7) # Ingredient Amount 1 Spaghetti 8 oz (half a box) 2 Butter 3 tablespoons 3 Garlic, minced 4 cloves 4 Honey 2 tablespoons 5 Soy sauce 1 tablespoon 6 Red pepper flakes ½ teaspoon 7 Parmesan cheese…
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Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

MiMo-V2-Omni703 words
Based on the pitch deck summary, here are the three weakest claims, an analysis of their weaknesses, and concrete suggestions for improvement. Weakest Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."
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Qwen3.8 Max Prime834 words
The 3 Weakest Claims in the MindMeld AI Pitch The TAM Calculation (Slide 4) The Claim: "We're targeting the 3.5 billion smartphone users worldwide. TAM: $180B." Why it's weak: This is a textbook example of TAM inflation that will immediately erode investor trust.
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Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

MiMo-V2-Omni558 words
🌱 Your 1-Month Health & Longevity Jumpstart Plan This plan focuses on sustainable, small changes in three core areas. The goal isn’t perfection—it’s building foundational habits that last. Week 1-2: Foundation & Awareness Focus on observation and gentle implementation. 1.
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Qwen3.8 Max Prime473 words
Your 1-Month Foundation Plan A simple, progressive plan built on three pillars. Each week, you add one small layer. No perfection required—just consistency. 🏃 Pillar 1: Movement Why: Even modest activity reduces all-cause mortality risk and improves mood, sleep, and energy within days.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

MiMo-V2-Omni1,005 words
Excellent question. This is a profound counterfactual that would rewrite the 20th century. Let's trace the implications, keeping in mind that the transistor's invention wasn't just a new device—it was the key that unlocked the information age. An earlier start accelerates everything built upon it.
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Qwen3.8 Max Prime2,943 words
The Transistor in 1920: A Counterfactual History Through 1980 Preamble: The Invention Itself The transistor's actual invention required quantum mechanical understanding of semiconductor behavior. In 1920, this theory didn't yet exist.
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Our Verdict
Qwen3.8 Max Prime
Qwen3.8 Max Prime
MiMo-V2-Omni
MiMo-V2-OmniRunner-up

Not enough votes to call it. On the specs, Qwen3.8 Max Prime has the edge: newer, bigger context window.

MiMo-V2-Omni costs 6.0x less per token.

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
10× cheaper
Output
$2.00
6.0× cheaper
Qwen3.8 Max Prime
Input
$4.00
Output
$12.00

MiMo-V2-Omni is cheaper on both: 10× input, 6.0× output.

Where to run it

1 host

MiMo-V2-Omni

No hosts listed on OpenRouter.

Qwen3.8 Max Prime1 host
HostInOutContextUptime
Alibaba Cloud$4.00 in·$12.00 out·1M·99.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

MiMo-V2-Omni is developed by Xiaomi while Qwen3.8 Max Prime is developed by Qwen. MiMo-V2-Omni has a 262K token context window vs Qwen3.8 Max Prime's 1.0M. You can compare their actual outputs across 19 challenges on Rival to see how they differ in practice.

It depends on your use case. MiMo-V2-Omni and Qwen3.8 Max Prime each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 19 challenges so you can judge which fits your needs best.

MiMo-V2-Omni costs $0.4/M input tokens and Qwen3.8 Max Prime costs $4/M input tokens. MiMo-V2-Omni is $3.60/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

This page shows a side-by-side comparison of MiMo-V2-Omni and Qwen3.8 Max Prime across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

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Same lab, same size, long tail

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Model pages

MiMo-V2-Omni logo
MiMo-V2-Omni53 outputs, specs and price
Qwen3.8 Max Prime logo
Qwen3.8 Max Prime19 outputs, specs and price
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