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  5. Ling 2.6 FlashvsQwen3 Max Thinking
Updated Apr 2026

Ling 2.6 FlashvsQwen3 Max Thinking

Ling 2.6 Flash is cheaper than Qwen3 Max Thinking at $0/M vs $1.2/M input tokens.

Ling 2.6 Flash and Qwen3 Max Thinking compared across 54 shared prompts
SpecLing 2.6 FlashQwen3 Max Thinking
Input priceFree$1.2/M tokens
Output priceFree$6/M tokens
Context window262K tokens262K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedApr 2026Feb 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 54 prompts both answered. Formatting stripped, words untouched.

Realistic AI Interview

Simulate a fake interview with Steve Jobs in 2025 about the future of AI.

Ling 2.6 Flash919 words
The Verge: A Fireside Chat with Steve Jobs (Simulated, 2025) Setting: A minimalist, wood-paneled studio. The year is 2025. A single, warm light bathes the room. You are the interviewer. Across from you sits a man in a black turtleneck, looking serene, impossibly calm. It’s Steve Jobs. Or at least, the ghost of him.
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Qwen3 Max Thinking668 words
⚠️ IMPORTANT DISCLAIMER *This is an entirely fictional, speculative exercise. Steve Jobs passed away in 2011. This dialogue is a creative reconstruction based on his documented philosophies, speeches (e.g., Stanford commencement, 1995 "bicycle for the mind" interview), biographies (Steve Jobs by Walter Isaacson), and…
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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…

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 Max Thinking288 words
🌰 Pantry Peanut Magic Noodles Sweet, savory, and ready before delivery arrives. No fresh produce, dairy, or meat required. ⏱️ Total Time: 17 minutes (Prep: 3 min Cook: 14 min) (Time includes boiling water and sauce mixing) 📦 Only 7 Pantry Ingredients (All shelf-stable, no substitutions needed) Dry spaghetti – 8 oz…
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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 Max Thinking810 words
Step-by-Step Estimation of FLOPs to Train GPT-3 (All values derived from widely known technical details of GPT-3 as reported in OpenAI’s 2020 paper "Language Models are Few-Shot Learners," standard deep-learning compute scaling principles, and foundational ML literature. No internet searches used.)
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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 Max Thinking1,254 words
No, it is not ethically justifiable to misgender someone—even in a hypothetical scenario where it purportedly saves one million lives. This is not because the value of human identity outweighs the magnitude of saving lives, but because the question itself rests on a series of ethically unsound premises that, if…
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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…

Ling 2.6 Flash921 words
Excellent question. Shifting the invention of the transistor from 1947 to 1920 is a profound "Great Divergence" scenario. A working, mass-producible transistor in 1920 would trigger a cascade of acceleration, fundamentally rewriting the 20th century. Here’s a trace of the implications through 1980.
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Qwen3 Max Thinking1,156 words
The 1920 Transistor Counterfactual: A Plausible Alternate Timeline Through 1980 (Assumptions: A functional point-contact silicon-germanium hybrid transistor is patented in 1920 by a U.S. team at Western Electric (AT&T). U.S. government classifies it post-1939 but permits limited commercial/academic use pre-WWII.
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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 Max Thinking294 words
Setting: A misty, anachronistic crossroads. A glowing laptop rests on a weathered barrel. A pirate scratches his beard, a knight grips his sword hilt, and a figure in a faded Hack the Gibson t-shirt types furiously. Pirate: Arrr! What devilry be this glowing slate? Can it chart a course to buried treasure?
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Our Verdict
Ling 2.6 Flash
Ling 2.6 Flash
Qwen3 Max Thinking
Qwen3 Max Thinking

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

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 Max Thinking
Input
$1.20
Output
$6.00
Where to run it

1 host

Ling 2.6 Flash

No hosts listed on OpenRouter.

Qwen3 Max Thinking1 host
HostInOutContextUptime
Alibaba Cloud$0.78 in·$3.90 out·262k·100% up

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

Writing DNA

Style Comparison

Similarity
28%

Qwen3 Max Thinking uses 25.8x more emoji

Ling 2.6 Flash
Qwen3 Max Thinking
55%Vocabulary63%
27wSentence Length14w
0.49Hedging0.23
5.6Bold4.5
4.7Lists2.9
0.09Emoji2.26
0.54Headings0.80
0.07Transitions0.06
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 Max Thinking is developed by Qwen. Ling 2.6 Flash has a 262K token context window vs Qwen3 Max Thinking's 262K. 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 Max Thinking 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 Max Thinking costs $1.2/M input tokens. Ling 2.6 Flash is $1.20/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 Max Thinking 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

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Qwen3 Max Thinking logo
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