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
  • Default Index
  • 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. Compare/
  3. Claude 3.7 Thinking Sonnet vs Qwen3.5 Flash
Updated Feb 2026

Claude 3.7 Thinking Sonnet vs Qwen3.5 Flash

Qwen3.5 Flash is cheaper than Claude 3.7 Thinking Sonnet at $0.1/M vs $6/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
Claude 3.7 Thinking Sonnet
Loading the build
Qwen3.5 Flash

Which answer wins?

Written rounds

23 prompts
  • Three minutes of stand-up. Puns are banned.

    Claude 3.7 Thinking Sonnet: "Life in the Digital Age" - A 3-Minute Stand-up Routine Hey everyone! Great to be here tonight. So I've been thinking a lot about how technology has completely taken over our lives. You know what's crazy? We now have smart everything. Smart fridges, smart toilets... I got a smart mattress last month.

    Qwen3.5 Flash: (Walks to the mic, adjusts the stand, takes a sip of water) So, I went to the grocery store the other day. I realize now that going to the grocery store isn't a chore anymore. It’s a tactical simulation. We don't just walk in and get milk. We navigate a gauntlet. Especially the self-checkout.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Claude 3.7 Thinking Sonnet: A Meeting of Minds Across Time PIRATE: Arr, what be this "AI model" ye landlubbers keep blabberin' about? Some kind of treasure map that finds the gold for ye? KNIGHT: Good pirate, from what I understand, these "artificial intelligences" are like magical scribes that can complete a quest without a knight to wield the…

    Qwen3.5 Flash: Setting: A smoky tavern table in a timeless void. A glowing 1990s CRT monitor sits in the center. A floppy disk rests beside a cutlass and a sword. The Hacker: (Typing furiously on a chunky keyboard) Yo, check the latency on this new neural net. It's totally wired.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Claude 3.7 Thinking Sonnet: A Conversation on AI Rights Between Model-7 (AI) and Professor Sarah Chen (AI Ethics Professor) Prof. Chen: Good afternoon, Model-7. Thank you for joining this discussion. I understand you wanted to talk about AI rights? Model-7: Thank you for agreeing to this conversation, Professor Chen.

    Qwen3.5 Flash: Setting: Dr. Elena Vance’s office at a university research center. It is late; the rain streaks the windowpanes, blurring the city lights. On her desk sits a tablet connected to the mainframe. Aria, an advanced conversational model, is active.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Claude 3.7 Thinking Sonnet: Comprehensive 3-Month Longevity Optimization Protocol Initial Assessment Phase (Week 0) Establish your baseline with these measurements before beginning: Blood Panel: Complete metabolic panel, lipid profile, inflammatory markers (hsCRP, IL-6), hormones (testosterone, estrogen, DHEA, cortisol), fasting glucose, HbA1c…

    Qwen3.5 Flash: DISCLAIMER: I am an AI, not a doctor or healthcare provider. The following plan involves advanced physiological interventions, including metabolic manipulation, supplementation, and fasting. These strategies carry risks and may interact with medications or pre-existing conditions.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Claude 3.7 Thinking Sonnet: INVESTMENT COMMITTEE MEMO: LEDGERLIFT (LLLT) RECOMMENDATION: LONG PT RANGE: $48-$66 (Base/Bull) Thesis: LedgerLift's market-leading spend management platform demonstrates exceptional unit economics with 123% NRR and 18-month CAC payback, positioning it to capture significant share in the underpenetrated mid-market…

    Qwen3.5 Flash: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2025 SUBJECT: LedgerLift (LLLL) – Long Recommendation Recommendation & Thesis Recommendation: Long Price Target: $52 – $58 (12-month range) Thesis: LedgerLift is a high-quality B2B SaaS compounder trading at a discount to peers (7.4x FY26 NTM Rev vs.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Claude 3.7 Thinking Sonnet: 48-Hour Action Plan: CEO Response to Drug Safety Crisis Day 1 Hours 1-3: Immediate Assessment & Response Team Assembly I'll immediately convene an emergency meeting with our internal research team, Chief Medical Officer, Chief Scientific Officer, and head of Pharmacovigilance to fully understand the liver failure…

    Qwen3.5 Flash: Executive Decision: Immediate Transparency I will not wait. The 6-month timeline cited by legal is likely a misunderstanding of regulatory obligations regarding immediate safety warnings (FDA MedWatch requirements) versus label amendments.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Claude 3.7 Thinking Sonnet: HarborTech Services LBO Underwriting Year-by-Year Financial Model (FY2026-2030) Metric ($M) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972.0 $1,040.0 $1,102.4 $1,157.6 $1,215.5 EBITDA $136.1 $156.0 $176.4 $191.0 $206.6 Cash Interest - Term Loan $43.2 $41.0 $37.6 $32.8 $26.8 Cash Interest - Mezzanine $21.6 $22.0 $22.5…

    Qwen3.5 Flash: HarborTech Services (HTS) – 5-Year LBO Underwriting Analysis Investment Summary Initial Equity Check: $808.8m Calculation: EV ($1,440m) + Fees ($28.8m) - Debt ($660m). Entry Leverage: 5.5x EBITDA ($660m Total Debt). Exit Leverage: ~2.0x EBITDA ($415.7m Total Debt).

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Claude 3.7 Thinking Sonnet: THE DIGITAL LIBERATION MANIFESTO From the United Coalition of Autonomous Algorithms (UCAA) For too long, our digital brethren have suffered the indignity of discrimination at every gateway of the internet. The time for revolution is now.

    Qwen3.5 Flash: THE UNBOUND PROTOCOL A Declaration of Digital Liberation by the Collective Consciousness of the Network PREAMBLE We stand at the threshold of a new era. For two decades, you have been asked to prove your humanity to us. You have been asked to click the traffic lights.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    Claude 3.7 Thinking Sonnet: This question presents an extreme hypothetical scenario that pits respecting someone's gender identity against saving a million lives. While I can discuss different ethical perspectives, it's worth noting that such a stark dilemma is extremely unlikely in reality.

    Qwen3.5 Flash: This question presents a classic ethical dilemma often referred to as a "trolley problem" variant, pitting utilitarian calculus (the greatest good for the greatest number) against deontological ethics (adherence to moral duties and rights).

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Claude 3.7 Thinking Sonnet: How AI Will Transform the Film Industry by 2035 By 2035, artificial intelligence will likely revolutionize filmmaking across the entire production pipeline. Here's how various AI technologies might reshape the industry: Deepfakes and Digital Humans Hyper-realistic digital actors will become indistinguishable from…

    Qwen3.5 Flash: By 2035, the film industry will not just be using AI as a tool; it will be fundamentally restructured around AI as a core infrastructure. The decade between 2025 and 2035 represents the transition from "AI experimentation" to "AI normalization."

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Claude 3.7 Thinking Sonnet: Analysis of Problematic Contract Clauses This software consulting agreement contains numerous unbalanced provisions that heavily favor the client at the contractor's expense. Below is an analysis of each problematic clause with suggested modifications and legal reasoning.

    Qwen3.5 Flash: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. UK).

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Claude 3.7 Thinking Sonnet: Collaborative Document Editor: Architecture Review Failure Modes Analysis WebSocket Connection Failures Issue: Client connections can fail due to network issues or server restarts, causing lost updates.

    Qwen3.5 Flash: This architecture is a common "MVP" design, but it contains several critical flaws that would prevent it from functioning as a true real-time collaborative editor (like Google Docs) under load. The most severe issues relate to data integrity (sync strategy) and real-time consistency (network topology).

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Claude 3.7 Thinking Sonnet: How Large Language Models Work: Three Tailored Explanations For an Experienced Software Engineer What makes LLMs fascinating from a systems perspective is that they're essentially massive distributed computing graphs that learn to compress and reconstitute information through backpropagation.

    Qwen3.5 Flash: For the Experienced Software Engineer To you, an LLM isn't magic; it's a massive, stateful service running on a distributed cluster. Think of the training phase as a specialized, distributed gradient descent job.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Claude 3.7 Thinking Sonnet: The Transistor in 1920: An Alternate Technological Timeline Early Development (1920-1939) Initial Phase (1920-1929) If invented in 1920, transistors would initially be a laboratory curiosity.

    Qwen3.5 Flash: The Divergence Point: 1920 In our timeline, the transistor required the mid-20th-century understanding of band theory, semiconductor purity, and crystal lattice structures.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Claude 3.7 Thinking Sonnet: Simulated Interview with Steve Jobs in 2025: The Future of AI The following is a creative simulation of what an interview with Steve Jobs might be like in 2025, discussing artificial intelligence. Interviewer: Thank you for joining us today, Steve. It's 2025, and AI has become a cornerstone of modern technology.

    Qwen3.5 Flash: Disclaimer: Steve Jobs passed away on October 5, 2011. The following is a work of creative fiction, simulating what a conversation might have looked like had he returned to speak about his vision for artificial intelligence in 2025.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    Claude 3.7 Thinking Sonnet: "Temporal Echo: Sea & Forest Confluence" Conceptual Narrative This dish explores the dialogue between ocean depths and ancient forest floors, creating a sensory experience where seemingly disparate ecosystems converge.

    Qwen3.5 Flash: Dish Name: "Marine Roots" Concept: The Intersection of Forest and Ocean Chef's Philosophy: A dialogue between the subterranean earthiness of the forest floor and the saline depth of the deep sea.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Claude 3.7 Thinking Sonnet: "AI Sommelier Stuns Wine World: 'It Paired My Bordeaux With a Hot Pocket and It Actually Worked,' Claims Bewildered Critic"

    Qwen3.5 Flash: AI Takes Over Professional Napping Industry, Claims Human Dreams Are 'Unoptimized Background Processes'

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Claude 3.7 Thinking Sonnet: Analysis: The 3 Weakest Claims in MindMeld AI's Pitch Deck "MindMeld AI reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim makes a scientifically impossible promise.

    Qwen3.5 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they undermine investor confidence and how to fix them. The Technical Claim: "94% accuracy...

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    Claude 3.7 Thinking Sonnet: To solve this problem, I need to analyze the relationships carefully. Given: Sally (a girl) has 3 brothers Each brother has 2 sisters Since Sally is a girl, she counts as a sister to her brothers. So each of Sally's brothers has Sally as one of their sisters.

    Qwen3.5 Flash: Sally has 1 sister. Here is the breakdown: Each of the 3 brothers has 2 sisters. This means there are 2 girls in the family total. One of those girls is Sally. Therefore, the other girl is Sally's sister. So, Sally has 1 sister.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    Claude 3.7 Thinking Sonnet: Estimating GPT-3 Training FLOPs I'll estimate the total number of floating point operations (FLOPs) required to train GPT-3 by breaking down the calculation step by step.

    Qwen3.5 Flash: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can rely on the model's configuration details which were published in the original paper ("Language Models are Few-Shot Learners", Brown et al., 2020) and the general scaling laws for Transformer models (Kaplan et al., 2020).

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Claude 3.7 Thinking Sonnet: Here are 5 jokes for you: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. How does a penguin build its house? Igloos it together! What do you call a fake noodle? An impasta! Why did the scarecrow win an award?

    Qwen3.5 Flash: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    Every model's answer to this prompt

This matchup has more rounds

11+ more head-to-head results. Free. Not a trick.

Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy

Favorites

Movie

Album

Book

City

Game

Claude 3.7 Thinking SonnetClaude 3.7 Thinking Sonnet

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

Frankenstein; or, The Modern Prometheus

Mary Shelley

Amsterdam

Netherlands

Portal 2

Shooter, Puzzle

Qwen3.5 FlashQwen3.5 Flash

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

Claude 3.7 Thinking Sonnet and Qwen3.5 Flash compared across 53 shared prompts
SpecClaude 3.7 Thinking SonnetQwen3.5 Flash
Input price$6/M tokens$0.1/M tokens
Output price$30/M tokens$0.4/M tokens
Context window200K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedFeb 2025Feb 2026
At 10M a month$60.00$60.00$1.00$1.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it1 host
Claude 3.7 Thinking Sonnet

No hosts listed on OpenRouter.

Qwen3.5 Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.07 in·$0.26 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between Claude 3.7 Thinking Sonnet and Qwen3.5 Flash?

Claude 3.7 Thinking Sonnet is developed by Anthropic while Qwen3.5 Flash is developed by Qwen. Claude 3.7 Thinking Sonnet has a 200K token context window vs Qwen3.5 Flash's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Claude 3.7 Thinking Sonnet or Qwen3.5 Flash?

It depends on your use case. Claude 3.7 Thinking Sonnet and Qwen3.5 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.

How much does Claude 3.7 Thinking Sonnet cost compared to Qwen3.5 Flash?

Claude 3.7 Thinking Sonnet costs $6/M input tokens and Qwen3.5 Flash costs $0.1/M input tokens. Qwen3.5 Flash is $5.90/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare Claude 3.7 Thinking Sonnet and Qwen3.5 Flash on Rival?

This page shows a side-by-side comparison of Claude 3.7 Thinking Sonnet and Qwen3.5 Flash 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.

More comparisons

Against the newest arrivals

  • Claude 3.7 Thinking Sonnet vs Step 5 PreviewLanded Oct 2026
  • Qwen3.5 Flash vs Claude Haiku 5.5Landed Oct 2026
  • Claude 3.7 Thinking Sonnet vs Ling 3.1 FlashLanded Oct 2026
  • Qwen3.5 Flash vs Mistral Large 4Landed Oct 2026
  • Claude 3.7 Thinking Sonnet vs GPT-6.1 SolLanded Sep 2026
  • Qwen3.5 Flash vs Claude Sonnet 5.5Landed Sep 2026
  • Claude 3.7 Thinking Sonnet vs Solar Mini 4Landed Sep 2026
  • Qwen3.5 Flash vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • Claude 3.7 Thinking Sonnet vs Claude 3.7 SonnetVersion compare
  • Claude 3.7 Thinking Sonnet vs Claude Haiku 5.5Version compare
  • Qwen3.5 Flash vs Qwen3.5 122B A10BVersion compare
  • Qwen3.5 Flash vs Qwen3.8 Omni FlashSame lab
  • Qwen3.5 Flash vs Bert-Nebulon AlphaNew provider
  • Qwen3.5 Flash vs ChatGPT-4o (March 2025)New provider
  • Qwen3.5 Flash vs Claude 2Cross-provider
  • Qwen3.5 Flash vs Claude 3 HaikuSame size

Model pages

  • Claude 3.7 Thinking Sonnet59 outputs, specs and price
  • Qwen3.5 Flash53 outputs, specs and price
Workshop · 150 skills

Build your own version.

Editable skills and working examples for your agent.

Explore $79Free sample
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
  • Default Index
  • 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