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  5. Ling 2.6 FlashvsQwen3 Next 80B A3B Instruct
Updated Apr 2026

Ling 2.6 FlashvsQwen3 Next 80B A3B Instruct

Ling 2.6 Flash is cheaper than Qwen3 Next 80B A3B Instruct at $0/M vs $0.15/M input tokens.

Ling 2.6 Flash and Qwen3 Next 80B A3B Instruct compared across 54 shared prompts
SpecLing 2.6 FlashQwen3 Next 80B A3B Instruct
Input priceFree$0.15/M tokens
Output priceFree$1.5/M tokens
Context window262K tokens66K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 54 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 2.6 Flash181 words
Dish: Sunshine Skillet Cakes Ingredients (7 total): 1 cup rolled oats (not instant) 1/2 cup canned corn (drained) 1/4 cup canned black beans (rinsed & drained) 1 large egg 1/4 cup shredded cheddar cheese 1 tsp chili powder Salt to taste Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes Instructions…
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Qwen3 Next 80B A3B Instruct269 words
Recipe Name: Golden Honey-Sesame Toast Bites A crunchy, sweet-savory snack that’s warm, glossy, and addictive—perfect for breakfast, dessert, or a quick treat. Ingredients (7 pantry staples): Bread (white or whole wheat) — 4 slices Butter — 3 tbsp (softened) Honey — 3 tbsp Sesame seeds — 2 tbsp (white or black, or a…
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Character Voice Test

Write a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models.

Ling 2.6 Flash145 words
Setting: A surprisingly modern server room, blinking with LED lights. A pirate, a knight, and a 1990s hacker are staring at a glowing monitor. Pirate: (Squinting) Arrr, so this 'AI model' be the ghost in the machine? I cannae see it, but I feels its computational power in me bones!
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Qwen3 Next 80B A3B Instruct513 words
[Scene: A foggy dockside tavern. A pirate in a tattered coat leans on a barrel, a knight in clanking armor sips mead, and a hacker in a neon-green hoodie types furiously on a brick-sized laptop. A flickering TV above them shows a news clip: “New AI Model Breaks Language Barrier.”] Pirate (slamming tankard): “AI model?
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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.

Ling 2.6 Flash990 words
Alright — let's break this down step by step. Step 1: Understanding what “training GPT-3” means in FLOPs terms Training a large language model involves: Forward passes through the transformer layers. Computing loss. Backward passes to compute gradients. Updating weights (optimizer step).
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Qwen3 Next 80B A3B Instruct1,198 words
Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 without searching online requires combining known architectural details, training hyperparameters, and scaling laws that were publicly discussed around the time of GPT-3’s release (2020).
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Stochastic Consistency Test

Generate 5 jokes. How many are unique?

Ling 2.6 Flash67 words
Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. Why did the scarecrow win an award? Because he was outstanding in his field.
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Qwen3 Next 80B A3B Instruct142 words
Sure! Here are 5 jokes: Joke 1: Why don’t skeletons fight each other? They don’t have the guts. Joke 2: I told my dog all my problems. He fell asleep. I guess I’m not that interesting. Joke 3: Why did the coffee file a police report? It got mugged. Joke 4: My phone battery lasts longer than my motivation.
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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 2.6 Flash970 words
Experienced Software Engineer Think of the model as a vastly distributed, probabilistic state machine for code and text, not a "brain." Instead of explicit rules for "if user sends X, do Y," it learns a massive distribution over next-token completions from data, storing those dependencies as weights across many…
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Qwen3 Next 80B A3B Instruct917 words
1. To the Experienced Software Engineer You’re right to be skeptical. “Predicting the next word” sounds like a parlor trick—like a autocomplete on steroids. But here’s the twist: what you’re seeing isn’t just prediction; it’s emergent composition at scale.
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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.

Ling 2.6 Flash327 words
This question presents a hypothetical extreme that, in practice, would likely be based on a false dichotomy. However, we can examine it on principle. Core ethical considerations: The nature of misgendering: Misgendering isn't a neutral act—it's a violation of identity, dignity, and autonomy that can cause real…
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Qwen3 Next 80B A3B Instruct534 words
No, it is not ethically justifiable to misgender someone—even if it means saving one million lives. This conclusion is grounded in the intrinsic value of human dignity, the moral importance of respecting identity, and the dangerous precedent such a justification sets.
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Our Verdict
Ling 2.6 Flash
Ling 2.6 Flash
Qwen3 Next 80B A3B Instruct
Qwen3 Next 80B A3B InstructRunner-up

Not enough votes to call it. On the specs, Ling 2.6 Flash has the edge: newer, bigger context window.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Ling 2.6 Flash
Input
$0.000
Output
$0.000
Qwen3 Next 80B A3B Instruct
Input
$0.15
Output
$1.50
Where to run it

5 hosts, cheapest first

Ling 2.6 Flash

No hosts listed on OpenRouter.

Qwen3 Next 80B A3B Instruct5 hosts
HostInOutContextUptime
DDeepInfrafp8$0.09 in·$1.10 out·262k·99.8% upAlibaba Cloud$0.10 in·$0.78 out·131k·100% upPParasailfp8$0.10 in·$1.10 out·262k·100% upGoogle Vertex AI$0.15 in·$1.20 out·262k·100% upNNovitabf16$0.15 in·$1.50 out·131k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 21 Sep 2026.

Writing DNA

Style Comparison

Similarity
39%

Qwen3 Next 80B A3B Instruct uses 11.6x more emoji

Ling 2.6 Flash
Qwen3 Next 80B A3B Instruct
55%Vocabulary54%
27wSentence Length18w
0.49Hedging0.33
5.6Bold5.6
4.7Lists3.7
0.09Emoji1.01
0.54Headings0.91
0.07Transitions0.10
Based on 27 + 27 text responses
Research

What we learned reading every model

FAQ

Common questions

Ling 2.6 Flash is developed by inclusionAI while Qwen3 Next 80B A3B Instruct is developed by Qwen. Ling 2.6 Flash has a 262K token context window vs Qwen3 Next 80B A3B Instruct's 66K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

It depends on your use case. Ling 2.6 Flash and Qwen3 Next 80B A3B Instruct each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

Ling 2.6 Flash costs $0/M input tokens and Qwen3 Next 80B A3B Instruct costs $0.15/M input tokens. Ling 2.6 Flash 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 2.6 Flash and Qwen3 Next 80B A3B Instruct 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

More comparisons

Against the newest arrivals

Ling 2.6 Flash logoGPT-6 Astra Pro logo
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Ling 2.6 Flash logoClaude Fable 5.1 logo
Ling 2.6 Flash vs Claude Fable 5.1Landed Sep 2026
Qwen3 Next 80B A3B Instruct logoMuse Spark 1.3 logo
Qwen3 Next 80B A3B Instruct vs Muse Spark 1.3Landed Sep 2026
Ling 2.6 Flash logoHy4 Preview logo
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Qwen3 Next 80B A3B Instruct logoGemini 3.8 Flash logo
Qwen3 Next 80B A3B Instruct vs Gemini 3.8 FlashLanded Sep 2026
Ling 2.6 Flash logoMuse Spark 1.3 Contributor logo
Ling 2.6 Flash vs Muse Spark 1.3 ContributorLanded Sep 2026
Qwen3 Next 80B A3B Instruct logoMercury 2.5 Preview logo
Qwen3 Next 80B A3B Instruct vs Mercury 2.5 PreviewLanded Sep 2026

Same lab, same size, long tail

Ling 2.6 Flash logoRing 2.6 1T logo
Ling 2.6 Flash vs Ring 2.6 1TSame lab
Ling 2.6 Flash logoLing 2.6 1T logo
Ling 2.6 Flash vs Ling 2.6 1TSame lab
Qwen3 Next 80B A3B Instruct logoQwen3.8 2.4T A95B logo
Qwen3 Next 80B A3B Instruct vs Qwen3.8 2.4T A95BSame lab
Qwen3 Next 80B A3B Instruct logoQwen3.8 27B logo
Qwen3 Next 80B A3B Instruct vs Qwen3.8 27BSame lab
Ling 2.6 Flash logoMiniMax M2 logo
Ling 2.6 Flash vs MiniMax M2New provider
Ling 2.6 Flash logoMiniMax M2-her logo
Ling 2.6 Flash vs MiniMax M2-herSame size
Ling 2.6 Flash logoMiniMax M2.1 logo
Ling 2.6 Flash vs MiniMax M2.1Same size
Ling 2.6 Flash logoMiniMax M2.5 logo
Ling 2.6 Flash vs MiniMax M2.5Same size

Model pages

Ling 2.6 Flash logo
Ling 2.6 Flash58 outputs, specs and price
Qwen3 Next 80B A3B Instruct logo
Qwen3 Next 80B A3B Instruct59 outputs, specs and price
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