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  5. Ling 3.0 FlashvsQwen3.6 27B
Updated Jul 2026

Ling 3.0 FlashvsQwen3.6 27B

Ling 3.0 Flash is cheaper than Qwen3.6 27B at $0.021/M vs $0.325/M input tokens.

Ling 3.0 Flash and Qwen3.6 27B compared across 15 shared prompts
SpecLing 3.0 FlashQwen3.6 27B
Input price$0.021/M tokens$0.325/M tokens
Output price$0.063/M tokens$3.25/M tokens
Context window262K tokens256K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Apr 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 15 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 Flash248 words
🍝 Honey Fire Twirls A sticky-sweet, spicy, savory pasta that comes together in minutes. 🧺 Ingredients (7 pantry staples) Spaghetti (or penne) — 8 oz Olive oil — 2 tablespoons Garlic, minced — 4 cloves Honey — 3 tablespoons Soy sauce — 2 tablespoons Red pepper flakes — ½ teaspoon (adjust to taste) Parmesan cheese…
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Qwen3.6 27B346 words
🍪 Midnight Crinkle Cookies These rich, fudgy cookies are the ultimate pantry rescue. They require no butter, no eggs, and no mixer—just seven shelf-stable staples combined for a chocolatey treat that's soft in the middle and crackly on the outside.
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Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

Ling 3.0 Flash2,623 words
48-Hour Action Plan: Responsible Disclosure of Serious Adverse Effect FOUNDATIONAL PRINCIPLE Before the hour-by-hour breakdown, the strategic and ethical framework must be established clearly: proactive, transparent disclosure is the only viable path.
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Qwen3.6 27B1,346 words
As CEO, my primary fiduciary and ethical duty is to patients, regulators, and long-term shareholder value. The "6-month reporting timeline" cited by legal is almost certainly a misunderstanding of regulatory processes (likely conflating initial adverse event reporting with full label amendment review).
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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 Flash1,129 words
For the Experienced Software Engineer Think of an LLM as a system that learns a massive, multidimensional routing table. When you built distributed systems, you learned patterns from traffic logs — which endpoints get hammered at 3am, which failure modes correlate, which request chains tend to cascade.
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Qwen3.6 27B1,091 words
For the Experienced Software Engineer Think of an LLM not as a simple autocomplete, but as a highly optimized, probabilistic state machine built on a dynamic routing architecture. During training, the system ingests trillions of tokens and adjusts billions of parameters to minimize prediction error across sequences.
Read the full answer

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

Ling 3.0 Flash2,291 words
Architecture Analysis: Real-Time Collaborative Document Editor WebSocket & Cross-Server Communication Issue: Siloed WebSocket Servers (Critical) Each API server only broadcasts changes to clients connected to that specific server.
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Qwen3.6 27B415 words
This architecture contains several critical flaws that will cause data loss, severe latency, security vulnerabilities, and scaling failures under real-world load. Below is a systematic breakdown of failure modes, race conditions, and bottlenecks, with targeted solutions and trade-offs. 🔹 I.
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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 Flash568 words
🌱 Your 1-Month Health & Longevity Starter Plan 🥦 1. Diet — Nourish, Don't Deprive Week 1: Awareness Keep a food journal — just track what you eat (no judgment). This alone builds mindful eating habits. Add, don't subtract — introduce one extra serving of vegetables per meal.
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Qwen3.6 27B766 words
Here is a simple, actionable 1-month plan designed for beginners. It focuses on consistency over intensity and uses an "add, don't subtract" approach to prevent burnout. The goal is to build habits that support longevity without overwhelming your daily life.
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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 3.0 Flash3,452 words
The 1920 Transistor: A Counterfactual Cascade Through 1980 This is a rich counterfactual. A 27-year acceleration of the transistor doesn't just move technology forward — it restructures the causal chains of the 20th century.
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Qwen3.6 27B1,446 words
To trace a counterfactual where the transistor is invented in 1920 rather than 1947, we must first acknowledge the scientific and industrial prerequisites: solid-state physics, crystal growth techniques, precision microfabrication, and materials science would need to mature decades earlier.
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Our Verdict
Ling 3.0 Flash
Ling 3.0 Flash
Qwen3.6 27B
Qwen3.6 27BRunner-up

Not enough votes to call it. On the specs, Ling 3.0 Flash has the edge: bigger model tier, newer.

Ling 3.0 Flash costs 52x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Ling 3.0 Flash
Input
$0.02
15× cheaper
Output
$0.06
52× cheaper
Qwen3.6 27B
Input
$0.33
Output
$3.25

Ling 3.0 Flash is cheaper on both: 15× input, 52× output.

Where to run it

8 hosts, cheapest first

Ling 3.0 Flash2 hosts
HostInOutContextUptime
NNovita$0.02 in·$0.06 out·262k·100% upDDeepInfrabf16$0.06 in·$0.18 out·131k·99.6% up
Qwen3.6 27B6 hosts
HostInOutContextUptime
CChutesfp8$0.30 in·$2.00 out·262k·91.7% upSSiliconFlowfp8$0.30 in·$3.20 out·262k·86.5% upPPhala$0.32 in·$2.70 out·262k·96% upDDeepInfrafp8$0.32 in·$3.20 out·262k·99.7% upVVenicefp8$0.33 in·$3.25 out·256k·95.9% upAlibaba Cloud$0.45 in·$2.70 out·262k·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 22 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Ling 3.0 Flash is developed by inclusionAI while Qwen3.6 27B is developed by Qwen. Ling 3.0 Flash has a 262K token context window vs Qwen3.6 27B's 256K. You can compare their actual outputs across 15 challenges on Rival to see how they differ in practice.

It depends on your use case. Ling 3.0 Flash and Qwen3.6 27B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 15 challenges so you can judge which fits your needs best.

Ling 3.0 Flash costs $0.021/M input tokens and Qwen3.6 27B costs $0.325/M input tokens. Ling 3.0 Flash is $0.30/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 and Qwen3.6 27B 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 logo
Ling 3.0 Flash16 outputs, specs and price
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