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  5. Ling 3.0 Flash Fin (free)vsQwen3.8 Omni Flash
Updated Sep 2026

Ling 3.0 Flash Fin (free)vsQwen3.8 Omni Flash

Ling 3.0 Flash Fin (free) is cheaper than Qwen3.8 Omni Flash at $0/M vs $0.15/M input tokens.

Ling 3.0 Flash Fin (free) and Qwen3.8 Omni Flash compared across 9 shared prompts
SpecLing 3.0 Flash Fin (free)Qwen3.8 Omni Flash
Input priceFree$0.15/M tokens
Output priceFree$0.47/M tokens
Context window262K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)Yes (1 provider)No
ReleasedAug 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…

Ling 3.0 Flash Fin (free)166 words
Midnight Molten Lava Cake Ingredients: All-purpose flour (4 tbsp) Granulated sugar (4 tbsp) Unsweetened cocoa powder (2 tbsp) Vegetable oil (3 tbsp) Water (2 tbsp) Vanilla extract (¼ tsp) Baking powder (¼ tsp) Instructions: Combine Dry Ingredients: In a standard microwave-safe mug, whisk together the flour, sugar…
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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…
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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.…

Ling 3.0 Flash Fin (free)961 words
The 3 Weakest Claims in the MindMeld AI Pitch 🚨 The $180B TAM Claim (Slide 4) Why it's weak: This is the most logically incoherent claim in the entire deck. The pitch states the BCI market is projected to reach $5.3B by 2030 (citing Grand View Research) — and then immediately claims a TAM of $180B.
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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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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…

Ling 3.0 Flash Fin (free)928 words
For the Experienced Software Engineer Here's the thing: the way you build a distributed system that "does the right thing" isn't by writing rules for every possible scenario — it's by designing the system so that correct behavior emerges from many simple, well-specified interactions.
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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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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…

Ling 3.0 Flash Fin (free)825 words
This 1-month plan is designed to build foundational habits without causing burnout. The golden rule of beginner health is "add before you subtract"—focus on adding good habits rather than punishing yourself by removing "bad" ones. Here is your simple, actionable 1-month plan focusing on Diet, Exercise, and Sleep.
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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Our Verdict
Ling 3.0 Flash Fin (free)
Ling 3.0 Flash Fin (free)
Qwen3.8 Omni Flash
Qwen3.8 Omni Flash

Not enough votes to call it. On the specs, nothing separates them.

Too close to call
API pricing

Cost per 1M tokens

Ling 3.0 Flash Fin (free)
Input
$0.000
Output
$0.000
Qwen3.8 Omni Flash
Input
$0.15
Output
$0.47
Where to run it

2 hosts

Ling 3.0 Flash Fin (free)1 host
HostInOutContextUptime
NNovita$0 in·$0 out·262k·100% 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

Ling 3.0 Flash Fin (free) is developed by inclusionAI while Qwen3.8 Omni Flash is developed by Qwen. Ling 3.0 Flash Fin (free) 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. Ling 3.0 Flash Fin (free) 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.

Ling 3.0 Flash Fin (free) costs $0/M input tokens and Qwen3.8 Omni Flash costs $0.15/M input tokens. Ling 3.0 Flash Fin (free) is $0.15/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 Ling 3.0 Flash Fin (free) 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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Model pages

Ling 3.0 Flash Fin (free) logo
Ling 3.0 Flash Fin (free)20 outputs, specs and price
Qwen3.8 Omni Flash logo
Qwen3.8 Omni Flash9 outputs, specs and price
Rival
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