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  5. Mistral Medium 3.1vsQwen3.8 Omni Flash
Updated Sep 2026

Mistral Medium 3.1vsQwen3.8 Omni Flash

Qwen3.8 Omni Flash is cheaper than Mistral Medium 3.1 at $0.15/M vs $0.4/M input tokens.

Mistral Medium 3.1 and Qwen3.8 Omni Flash compared across 9 shared prompts
SpecMistral Medium 3.1Qwen3.8 Omni Flash
Input price$0.4/M tokens$0.15/M tokens
Output price$2/M tokens$0.47/M tokens
Context window131K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedAug 2025Sep 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…

Mistral Medium 3.1261 words
Dish Name: "Golden Crisp Honey-Nut Banana Bites" A warm, gooey, and crunchy treat that’s quick to make with just 7 pantry staples! Perfect for breakfast, a snack, or dessert. Ingredients (Serves 2-3) 2 ripe bananas (the spottier, the sweeter!)
Read the full answer
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

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…

Mistral Medium 3.11,160 words
1. For the Skeptical Software Engineer (Focus: Systems design, scalability, and why "next-word prediction" isn’t as dumb as it sounds.) You’re right to be skeptical—if someone told you that a system as complex as a distributed database was just "predicting the next byte," you’d laugh them out of the room.
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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.
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…

Mistral Medium 3.1730 words
Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity, focusing on three key areas: diet, movement, and sleep. Each week builds gradually to create sustainable habits without overwhelm. Core Principles Start small – Focus on consistency over perfection.
Read the full answer
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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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.…

Mistral Medium 3.1726 words
Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations and suggested improvements: 1. Weak Claim: "Works with any language, any device." (Slide 3 – Solution) Why it’s weak: Overly broad and unverified: Claiming compatibility with "any language" is implausible without evidence.
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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.
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Our Verdict
Qwen3.8 Omni Flash
Qwen3.8 Omni Flash
Mistral Medium 3.1
Mistral Medium 3.1Runner-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

Mistral Medium 3.1
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

2 hosts

Mistral Medium 3.11 host
HostInOutContextUptime
Mistral$0.40 in·$2.00 out·131k·99.9% up
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

Mistral Medium 3.1 is developed by Mistral AI while Qwen3.8 Omni Flash is developed by Qwen. Mistral Medium 3.1 has a 131K 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. Mistral Medium 3.1 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.

Mistral Medium 3.1 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 Mistral Medium 3.1 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.

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