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  5. MiMo-V2-OmnivsQwen3.8 Omni Flash
Updated Sep 2026

MiMo-V2-OmnivsQwen3.8 Omni Flash

Qwen3.8 Omni Flash is cheaper than MiMo-V2-Omni at $0.15/M vs $0.4/M input tokens.

MiMo-V2-Omni and Qwen3.8 Omni Flash compared across 9 shared prompts
SpecMiMo-V2-OmniQwen3.8 Omni Flash
Input price$0.4/M tokens$0.15/M tokens
Output price$2/M tokens$0.47/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 4 of the 9 prompts both answered. Formatting stripped, words untouched.

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 Omni Flash175 words
Buttery Cloud Pancakes A soft, golden pancake stack made with just 7 pantry staples—no special mix-ins, no fancy tools, just simple comfort. Ingredients All-purpose flour Granulated sugar Baking powder Fine salt Milk Egg Butter Prep Time 10 minutes Cook Time 12 minutes Serves 2–3 Instructions In a bowl, whisk together…
Read the full answer

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."
Read the full answer
Qwen3.8 Omni Flash2,971 words
The three weakest claims—ranked by how likely they are to fail investor diligence—are: “94% accuracy… works with any language, any device.” “TAM: $180B” based on 3.5B smartphone users. “FDA clearance” consuming 40% of the Series A raise.
Read the full answer

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 Omni Flash712 words
A Simple 1-Month Health & Longevity Starter Plan Goal: Build sustainable habits—not perfection—around diet, exercise, and recovery/sleep. Time commitment: Small daily actions plus 2–3 short workouts per week. The 3 Key Areas Diet: Add more good foods before restricting Beginner rule: Focus on adding, not removing.
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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 Omni Flash913 words
For the experienced software engineer A large language model is best thought of as a gigantic, parameterized probabilistic function that maps a sequence of tokens to a probability distribution over the next token.
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Our Verdict
Qwen3.8 Omni Flash
Qwen3.8 Omni Flash
MiMo-V2-Omni
MiMo-V2-OmniRunner-up

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

Qwen3.8 Omni Flash costs 4.3x less per token.

Too close to call
API pricing

Cost per 1M tokens

MiMo-V2-Omni
Input
$0.40
Output
$2.00
Qwen3.8 Omni Flash
Input
$0.15
2.7× cheaper
Output
$0.47
4.3× cheaper

Qwen3.8 Omni Flash is cheaper on both: 2.7× input, 4.3× output.

Where to run it

1 host

MiMo-V2-Omni

No hosts listed on OpenRouter.

Qwen3.8 Omni Flash1 host
HostInOutContextUptime
Alibaba Clouddegraded$0.15 in·$0.47 out·1M·99% 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 Omni Flash is developed by Qwen. MiMo-V2-Omni has a 262K token context window vs Qwen3.8 Omni Flash's 1.0M. You can compare their actual outputs across 9 challenges on Rival to see how they differ in practice.

It depends on your use case. MiMo-V2-Omni and Qwen3.8 Omni Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 9 challenges so you can judge which fits your needs best.

MiMo-V2-Omni costs $0.4/M input tokens and Qwen3.8 Omni Flash costs $0.15/M input tokens. Qwen3.8 Omni Flash is $0.25/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 Omni Flash 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.

Keep exploring

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Same lab, same size, long tail

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MiMo-V2-Omni logoGPT-6 Luna Pro logo
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MiMo-V2-Omni logoGPT-6 Sol logo
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Model pages

MiMo-V2-Omni logo
MiMo-V2-Omni53 outputs, specs and price
Qwen3.8 Omni Flash logo
Qwen3.8 Omni Flash9 outputs, specs and price
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