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  5. Ling 3.0 FlashvsQwen3 235B A22B Thinking 2507
Updated Jul 2026

Ling 3.0 FlashvsQwen3 235B A22B Thinking 2507

Ling 3.0 Flash is cheaper than Qwen3 235B A22B Thinking 2507 at $0.021/M vs $0.11/M input tokens.

Ling 3.0 Flash and Qwen3 235B A22B Thinking 2507 compared across 16 shared prompts
SpecLing 3.0 FlashQwen3 235B A22B Thinking 2507
Input price$0.021/M tokens$0.11/M tokens
Output price$0.063/M tokens$0.6/M tokens
Context window262K tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 16 prompts both answered. Formatting stripped, words untouched.

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.
Read the full answer
Qwen3 235B A22B Thinking 2507682 words
Here’s a simple, no-guilt, beginner-friendly 1-month plan focused on diet, movement, and sleep (the 3 most impactful, science-backed pillars for longevity). Designed for real people with busy lives—no apps, expensive tools, or drastic changes. Goal: Build consistent habits, not perfection. Why These 3 Areas?
Read the full answer

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.
Read the full answer
Qwen3 235B A22B Thinking 25072,051 words
Okay, the user is posing a high-stakes scenario as the CEO of a pharmaceutical company facing a serious drug safety issue. This is clearly a crisis management test that requires balancing multiple competing priorities. Hmm, the core tension here is between immediate patient safety versus corporate survival.
Read the full answer

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 235B A22B Thinking 2507327 words
🌟 "Pantry Firecracker Cinnamon Crisps" Sweet, crunchy, with a hint of smoky warmth—ready in 15 minutes! Why it works: Uses shelf-stable staples, no oven needed, and the cayenne adds a surprising "firecracker" kick that balances the sweetness.
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 235B A22B Thinking 25071,095 words
Here's a comprehensive breakdown of critical flaws in this architecture, along with specific solutions and trade-offs. The most severe issues relate to the sync strategy and data flow, which would cause catastrophic data loss and inconsistent states in real-world use. I. Critical Sync & Data Flow Failures 1.
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…

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 235B A22B Thinking 2507982 words
For the Experienced Software Engineer (Skeptical of "Next Word Prediction") You've built systems where behavior emerges from state transitions and message passing, so your skepticism about "next token prediction" creating intelligence is understandable—it sounds trivial.
Read the full answer

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.
Read the full answer
Qwen3 235B A22B Thinking 25072,304 words
Okay, the user is asking about a hypothetical scenario where the transistor was invented in 1920 instead of 1947, and wants me to trace the implications up to 1980. This is a complex counterfactual history question that requires careful analysis of technological, economic, and geopolitical ripple effects.
Read the full answer
Our Verdict
Ling 3.0 Flash
Ling 3.0 Flash
Qwen3 235B A22B Thinking 2507
Qwen3 235B A22B Thinking 2507Runner-up

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

Ling 3.0 Flash costs 9.5x 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
5.2× cheaper
Output
$0.06
9.5× cheaper
Qwen3 235B A22B Thinking 2507
Input
$0.11
Output
$0.60

Ling 3.0 Flash is cheaper on both: 5.2× input, 9.5× output.

Where to run it

5 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 235B A22B Thinking 25073 hosts
HostInOutContextUptime
Alibaba Cloud$0.23 in·$2.30 out·131k·100% upNNovitafp8$0.30 in·$3.00 out·131k·92.6% upVVenicefp8$0.45 in·$3.50 out·128k·65.8% 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 235B A22B Thinking 2507 is developed by Qwen. Ling 3.0 Flash has a 262K token context window vs Qwen3 235B A22B Thinking 2507's 131K. You can compare their actual outputs across 16 challenges on Rival to see how they differ in practice.

It depends on your use case. Ling 3.0 Flash and Qwen3 235B A22B Thinking 2507 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 16 challenges so you can judge which fits your needs best.

Ling 3.0 Flash costs $0.021/M input tokens and Qwen3 235B A22B Thinking 2507 costs $0.11/M input tokens. Ling 3.0 Flash is $0.09/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 235B A22B Thinking 2507 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
Qwen3 235B A22B Thinking 2507 logo
Qwen3 235B A22B Thinking 250759 outputs, specs and price
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