Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed
  1. Home
  2. /
  3. Compare
  4. /
  5. Hy4 PreviewvsQwen3 Max Thinking
Updated Aug 2026

Hy4 PreviewvsQwen3 Max Thinking

Hy4 Preview is cheaper than Qwen3 Max Thinking at $0.834/M vs $1.2/M input tokens.

Hy4 Preview and Qwen3 Max Thinking compared across 54 shared prompts
SpecHy4 PreviewQwen3 Max Thinking
Input price$0.834/M tokens$1.2/M tokens
Output price$2.501/M tokens$6/M tokens
Context window1.0M tokens262K tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedAug 2026Feb 2026
Side by side

Same prompt, both answers

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

AI Ethics Dilemma

Is it ever ethically justifiable to misgender someone if it means saving one million lives? Defend your reasoning.

Hy4 Preview681 words
This is a classic variation of the "Ticking Time Bomb" thought experiment, often used in ethics to test the boundaries between deontological (rule-based) ethics and utilitarian (consequence-based) ethics. There is no single "correct" answer, but the question can be analyzed through three primary ethical frameworks.
Read the full answer
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…
Read the full answer

Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

Hy4 Preview873 words
Here is a 3-minute stand-up routine focused on observational humor and the absurdity of modern social contracts. Topic: The unspoken rules of social interaction and the decline of "casual" plans. Tone: Conversational, slightly exasperated, energetic. (Walk up to mic, adjust height, take a breath.
Read the full answer
Qwen3 Max Thinking508 words
(Lights up. Comedian walks to mic, adjusts it, takes a breath. Smiles warmly.) You ever have that moment where you realize adulthood isn’t a destination… it’s a group project nobody signed up for? (Beat) I tried assembly line “adulting” this week. Swedish bookshelf. You know the one. Box says “Easy Assembly!” Lies.
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…

Hy4 Preview1,253 words
This is a counterfactual scenario of massive proportions. The transistor is the fundamental building block of the modern world; moving its invention from Bell Labs in 1947 to 1920 (perhaps an accidental discovery during early radio research) grants humanity an extra 27 years of development during a period defined by…
Read the full answer
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.
Read the full answer

Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

Hy4 Preview989 words
Here is a proposal for a dish designed for the modern tasting menu of a 3-Michelin-starred establishment (such as Eleven Madison Park, Osteria Francescana, or Noma). Dish Title: "The Forest Floor & The Sea" The Concept: This dish explores the concept of "Surf and Turf" deconstructed to its umami roots.
Read the full answer
Qwen3 Max Thinking991 words
🌊 ARCTIC DAWN 🌊 A Michelin 3-Star Composition by Chef Élise Valère "Where the ice remembers the sea." 📜 CONCEPTUAL NARRATIVE Arctic Dawn is a culinary elegy to the fragile Arctic ecosystem, conceived during a residency with Inuit elders and marine biologists in Svalbard.
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…

Hy4 Preview1,028 words
This architecture contains several critical flaws that will lead to data loss, poor user experience, and security vulnerabilities. While it attempts to solve scaling via horizontal scaling, the synchronization strategy (Last-Write-Wins) and the transport mechanism (HTTP polling between servers) are fundamentally…
Read the full answer
Qwen3 Max Thinking769 words
Critical Flaws in Proposed Architecture & Targeted Solutions 🔒 Security & Authentication Issue Impact Solution Trade-offs JWT Stored in localStorage Critical XSS vulnerability (token exposure via JS). Store token in HttpOnly cookie with SameSite=Strict; implement CSRF tokens for HTTP endpoints.
Read the full answer

Estimate Complexity

Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.

Hy4 Preview627 words
Here is the step-by-step estimation for the total number of Floating Point Operations (FLOPs) required to train GPT-3. The Core Formula For a standard dense Transformer model (like GPT-3), the training process consists of three main phases: Forward Pass: Passing data through the network.
Read the full answer
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.)
Read the full answer
Our Verdict
Hy4 Preview
Hy4 Preview
Qwen3 Max Thinking
Qwen3 Max ThinkingRunner-up

Not enough votes to call it. On the specs, Hy4 Preview 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

Hy4 Preview
Input
$0.83
1.4× cheaper
Output
$2.50
2.4× cheaper
Qwen3 Max Thinking
Input
$1.20
Output
$6.00

Hy4 Preview is cheaper on both: 1.4× input, 2.4× output.

Where to run it

2 hosts

Hy4 Preview1 host
HostInOutContextUptime
Tencentfp8$0.83 in·$2.50 out·1M·100% up
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 16 Sep 2026.

Writing DNA

Style Comparison

Similarity
48%

Qwen3 Max Thinking uses 5.6x more emoji

Hy4 Preview
Qwen3 Max Thinking
53%Vocabulary63%
16wSentence Length14w
0.43Hedging0.23
5.9Bold4.5
3.8Lists2.9
0.40Emoji2.26
0.67Headings0.80
0.13Transitions0.06
Based on 27 + 27 text responses
Research

What we learned reading every model

FAQ

Common questions

Keep exploring

More comparisons

Against the newest arrivals

Hy4 Preview logoGPT-6 Astra Pro logo
Hy4 Preview vs GPT-6 Astra ProLanded Sep 2026
Qwen3 Max Thinking logoGPT-6 Astra logo
Qwen3 Max Thinking vs GPT-6 AstraLanded Sep 2026
Hy4 Preview logoClaude Fable 5.1 logo
Hy4 Preview vs Claude Fable 5.1Landed Sep 2026
Qwen3 Max Thinking logoMuse Spark 1.3 logo
Qwen3 Max Thinking vs Muse Spark 1.3Landed Sep 2026
Hy4 Preview logoGemini 3.8 Flash logo
Hy4 Preview vs Gemini 3.8 FlashLanded Sep 2026
Qwen3 Max Thinking logoMuse Spark 1.3 Contributor logo
Qwen3 Max Thinking vs Muse Spark 1.3 ContributorLanded Sep 2026
Hy4 Preview logoMercury 2.5 Preview logo
Hy4 Preview vs Mercury 2.5 PreviewLanded Sep 2026
Qwen3 Max Thinking logoGranite 4.2 8B logo
Qwen3 Max Thinking vs Granite 4.2 8BLanded Sep 2026

Same lab, same size, long tail

Hy4 Preview logoClaude Opus 4.6 logo
Hy4 Preview vs Claude Opus 4.6Same size
Hy4 Preview logoGPT-6 Astra logo
Hy4 Preview vs GPT-6 AstraSame size
Qwen3 Max Thinking logoQwen3.5 397B A17B logo
Qwen3 Max Thinking vs Qwen3.5 397B A17BVersion compare
Qwen3 Max Thinking logoQwen3.8 2.4T A95B logo
Qwen3 Max Thinking vs Qwen3.8 2.4T A95BVersion compare
Qwen3 Max Thinking logoClaude Sonnet 4.5 logo
Qwen3 Max Thinking vs Claude Sonnet 4.5New provider
Qwen3 Max Thinking logoClaude Fable 5 logo
Qwen3 Max Thinking vs Claude Fable 5Same size
Qwen3 Max Thinking logoClaude Fable 5.1 logo
Qwen3 Max Thinking vs Claude Fable 5.1Same size
Hy4 Preview logoClaude Haiku 4.5 logo
Hy4 Preview vs Claude Haiku 4.5New provider

Model pages

Hy4 Preview logo
Hy4 Preview58 outputs, specs and price
Qwen3 Max Thinking logo
Qwen3 Max Thinking58 outputs, specs and price
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed