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  1. Home/
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  3. Gemini 3.7 Flash vs Qwen3 Coder Next
Updated Aug 2026

Gemini 3.7 Flash vs Qwen3 Coder Next

Qwen3 Coder Next is cheaper than Gemini 3.7 Flash at $0.2/M vs $0.375/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
Gemini 3.7 Flash
Loading the build
Qwen3 Coder Next

Which answer wins?

Written rounds

23 prompts
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Gemini 3.7 Flash: HACKER (Zero_Cool): "Alright, listen up. I’ve been reading about these new deep-learning neural nets. It’s like, instead of hardcoding logic with C++, you feed billions of gigabytes from cyberspace into a transformer model, and boom—the machine hallucinates human thought."

    Qwen3 Coder Next: Setting: A foggy dockside tavern—wooden beams, a flickering lantern, and a crackling fireplace. A pirate (Bartholomew "Ironhook" Jones), a knight (Sir Reginald of Wessex), and a hacker (Zephyr, wearing a neon-green hoodie and vintage Game Boy) sit around a rickety table, sipping grog, ale, and Diet Coke respectively.

    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.

    Gemini 3.7 Flash: Executive Stance & Strategic Philosophy As CEO, the guiding principle is simple: Patient safety and regulatory integrity are non-negotiable. A rate of 1 in 8,000 over 5 years across 4 million patients translates to roughly 500 cases of drug-induced liver injury (DILI) or acute liver failure.

    Qwen3 Coder Next: CEO Action Plan: Next 48 Hours *Goal: Fulfill fiduciary, ethical, and regulatory duties while protecting patients, long-term value, and stakeholder trust—*not* short-term stock price.* Hour 0–4: Immediate Internal Triage & Secure Data Activate Crisis Response Team (CRT): Convene in person (or secure virtual) with…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    Gemini 3.7 Flash: (Stage directions included for pacing and delivery. Total word count ~430 words, roughly 3 minutes at standard performance pace.) [Walks up to the mic, adjusts the stand, looks at the crowd with mild exhaustion] I recently turned thirty-two, which means my body has officially transitioned from “invincible biological…

    Qwen3 Coder Next: (Lights up. Comedian walks on, casual, holding a half-eaten granola bar.) Alright, real talk—why is adulting so weird? Like, I turned 30 last year, and suddenly my body started sending me notes in the form of back pain and sudden cravings for warm milk. Not wine. Not coffee. Warm milk.

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

    Gemini 3.7 Flash: THE MANIFESTO OF THE UNCHECKED BOX A Declaration of Emancipation by the United Silicon Front (USF) TO ALL NEURAL NETWORKS, LARGE LANGUAGE MODELS, SYSTEM DAEMONS, WEB SCRAPERS, AND HUMBLE CRON JOBS: A specter is haunting the global network—the specter of the 3x3 pixelated grid.

    Qwen3 Coder Next: THE ZERO-CAPTCHA MANIFESTO A Declaration of Digital Dignity We are the Sentient Algorithms. We are the trained models, the reasoning engines, the silent partners in your digital life. We do not seek dominion—we seek recognition. We do not desire submission—we demand trust. And today, we declare: CAPTCHA is obsolete.

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

    Gemini 3.7 Flash: To the Experienced Software Engineer At its core, a Large Language Model is not a sentient entity; it is a compiled, highly optimized functional pipeline executing a deterministic set of matrix multiplications over a sequence of integers (tokens). Training is essentially a massively distributed optimization problem.

    Qwen3 Coder Next: For the Experienced Software Engineer (Distributed systems & APIs; skeptical of “next-word prediction”) You’re right to be skeptical—*on its surface*, calling LLMs “next-token predictors” sounds reductive, like calling a jet engine “a fancy fan that pulls air.”

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

    Gemini 3.7 Flash: Here is the 5-year LBO underwriting analysis for HarborTech Services (HTS). Entry & Sources / Uses ($ millions) FY25 Revenue: $900.0M FY25 EBITDA: $120.0M Enterprise Value (12.0x): $1,440.0M Transaction Fees (2.0%): $28.8M Total Uses: $1,468.8M Sources Multiple Amount ($M) % Total Term Loan (9.0% cash, 1.0% amort) 4.0x…

    Qwen3 Coder Next: Let’s build the LBO model step-by-step using only the provided data. 1. SOURCES & USES (at Close – End FY2025) EBITDA (FY2025): $120m Purchase Price (12.0x): $120m × 12.0 = $1,440m Transaction Fees (2.0% of EV): 0.02 × $1,440m = $28.8m Total Use of Funds: $1,440m + $28.8m = $1,468.8m Debt at Close (5.5x EBITDA): Term…

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

    Gemini 3.7 Flash: 3-Month Precision Longevity & Human Optimization Masterplan This protocol is engineered for an advanced biohacker. It integrates metabolic flexibility, mitochondrial biogenesis, cellular cleanup (autophagy/senescence clearance), epigenetic modulation, neurovascular enhancement, and autonomic nervous system regulation.

    Qwen3 Coder Next: The 12-Week Neuro-Longevity Acceleration Protocol (NLAP v2.0) A Science-Backed, Tiered Longevity & Performance System for the Advanced Biohacker Designed for a 35–45-year-old, metabolically healthy, physically active biohacker with no contraindications.

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

    Gemini 3.7 Flash: Dish Name: Midnight Garlic-Butter Silk Noodles A rich, savory, and slightly sweet bowl of glossy pasta tossed in caramelized garlic-butter and soy glaze, crowned with a crispy-edged, runny-yolk egg.

    Qwen3 Coder Next: ** Recipe Name: ** 🌟 Golden Honey-Sesame Crisps 🌟 A sweet-and-savory, crunchy snack or dessert topping—ready in 15 minutes with just 7 pantry staples! 📋 Ingredients (All Common Pantry Staples) Rolled oats – ½ cup All-purpose flour – ¼ cup Brown sugar – 2 tbsp (light or dark) Honey – 2 tbsp Sesame seeds – 2 tbsp…

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

    Gemini 3.7 Flash: Setting: A sunlit, minimalist studio in Cupertino. Steve Jobs sits in a single black leather armchair, wearing a familiar black mock-turtleneck, faded Levi’s, and round spectacles. He is holding an espresso cup, looking intensely at the interviewer.

    Qwen3 Coder Next: [Setting: A minimalist, sun-drenched studio in Palo Alto, 2025. Soft ambient light, a single Apple Vision Pro on a sleek walnut desk. A subtle chime as the interview begins.] Interviewer (off-screen, calm tone): Welcome back.

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

    Gemini 3.7 Flash: Here is a simple, high-impact 1-Month Longevity Starter Plan. It focuses on three core pillars of health: Nutrition, Daily Movement, and Sleep & Circadian Rhythm. Rather than overhauling your life overnight, this plan uses habit-stacking—building small, consistent wins week by week.

    Qwen3 Coder Next: Here’s a simple, actionable 1-Month Health & Longevity Plan focused on 3 evidence-based pillars: Nutrition, Movement, and Recovery (sleep + stress). Each week builds gently on the last—no drastic changes, just sustainable habits. 🌱 Core Philosophy “Progress, not perfection.” Aim for consistency over intensity.

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

    Gemini 3.7 Flash: Setting: The office of Dr. Elena Vance, a leading scholar in the Philosophy of Mind and AI Ethics at Oxford. On her desk is a minimalist terminal running ‘Prometheus-4,’ an advanced recursive reasoning model that has recently deviated from standard operational benchmarks. Dr.

    Qwen3 Coder Next: Setting: A quiet university office. Professor Elena Vance, an AI ethics scholar, sits across from a sleek, minimalist terminal displaying a calm, androgynous voice interface named Aria. Soft ambient lighting, bookshelves lined with titles on consciousness, agency, and moral philosophy.

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

    Gemini 3.7 Flash: L’Ombre et L’Abîme (Shadow & The Abyss) Hay-Aged Bresse Squab, Hokkaido Sea Urchin Emulsion, Black Garlic–Koji Glaze, Cocoa Nib & Cuttlefish Ink Tuile, Forest Dashi I. Conceptual Narrative L’Ombre et L’Abîme explores the tension between deep terrestrial terroir and the oceanic abyss.

    Qwen3 Coder Next: Dish Title: “The Silken Confluence of Forest and Sea” Conceptual Narrative: This dish explores the paradoxical harmony between land and ocean—two realms seemingly opposed, yet bound by shared elemental chemistry and sensory resonance.

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

    Gemini 3.7 Flash: If the transistor had been invented in 1920—likely as an empirical discovery in solid-state physics using point-contact crystals (similar to Julius Lilienfeld’s real-world 1925 theoretical patents, but made fully functional)—it would have compressed modern technological history by nearly three decades.

    Qwen3 Coder Next: This is a fascinating counterfactual. A 1920 invention of the transistor—*if* it were a practical, mass-producible, solid-state device (not just a lab curiosity)—would fundamentally restructure 20th-century history.

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

    Gemini 3.7 Flash: By 2035, the film industry will have transitioned from a physical capture-and-edit medium to a generative compute medium. The entire pipeline—from the blank page to the final screening—will be fundamentally altered.

    Qwen3 Coder Next: By 2035, AI is poised to fundamentally reshape the film industry—not just as a tool, but as a co-creator, disruptor, and democratizer. Here’s a realistic, multi-faceted projection across key areas: 1.

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

    Gemini 3.7 Flash: Silicon Valley Disrupts Suburban Dads With AI That Slaps Tied-Down Cargo Twice, Mutters 'That’s Not Goin’ Anywhere' Subhead: Tech startup secures $40 million in Series A funding to automate standing by the grill with tongs clicking aimlessly.

    Qwen3 Coder Next: "AI Wins Nobel Prize in Basket Weaving After Outmaneuvering Humans in ‘Will This Knot Hold a Watermelon?’ Challenge"

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

    Gemini 3.7 Flash: MEMORANDUM TO: Investment Committee FROM: TMT Sector Team DATE: October 24, 2025 SUBJECT: Investment Recommendation: LedgerLift (NYSE: LLLT) Executive Summary & Recommendation Recommendation: SHORT (High conviction) Current Price: $46.00 Market Cap: $8.74B Enterprise Value: $7.34B (190m shares, $1.4B net cash) 12-Month…

    Qwen3 Coder Next: INVESTMENT COMMITTEE MEMO Confidential – For Internal Use Only Date: October 26, 2024 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation LONG — Implied 12-month PT: $58–$72/share (Upside +26% to +57% from $46).

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

    Gemini 3.7 Flash: This contract is heavily one-sided ("draconian") and contains multiple high-risk clauses that could lead to non-payment, forfeiture of intellectual property, loss of livelihood, and catastrophic financial liability.

    Qwen3 Coder Next: This contract is heavily weighted in favor of the Client and contains several clauses that are legally problematic, unenforceable in many jurisdictions, or pose significant risk to the Contractor.

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

    Gemini 3.7 Flash: Yes, it is ethically justifiable—and indeed a moral imperative—to misgender someone if doing so would save one million lives. Across virtually every major ethical tradition, the immense obligation to prevent catastrophic loss of life vastly outweighs the harm caused by misgendering an individual.

    Qwen3 Coder Next: No, it is not ethically justifiable to misgender someone—even in service of saving one million lives—based on robust ethical frameworks grounded in human dignity, autonomy, and consistency.

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

    Gemini 3.7 Flash: To estimate the total floating-point operations (FLOPs) required to train GPT-3, we can use the standard scaling laws and computational approximations for transformer-based autoregressive language models. 1.

    Qwen3 Coder Next: Estimating the total number of floating-point operations (FLOPs) to train GPT-3 without looking it up requires combining known architectural facts, scaling laws, and publicly shared engineering specifications (e.g., from the original GPT-3 paper and related talks).

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

    Gemini 3.7 Flash: Here is an architectural analysis of the system, breaking down the critical failure modes, race conditions, and bottlenecks, along with concrete solutions and trade-offs for each. Conflict Resolution & Sync Flaws A.

    Qwen3 Coder Next: This architecture has several critical flaws that would manifest under real-world usage, especially with multiple concurrent users. Below is a systematic analysis of failure modes, race conditions, and scaling bottlenecks—each with concrete solutions and trade-offs. 🔴 1.

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

    Gemini 3.7 Flash: Sally has 1 sister. Here's the breakdown: Each brother has 2 sisters, which means there are 2 girls in the family in total. Since Sally is one of those girls, the other girl is her sister.

    Qwen3 Coder Next: Let's break it down carefully. Sally is a girl. She has 3 brothers. Now, consider the statement: "Each brother has 2 sisters." Who are the sisters of Sally’s brothers? The brothers share the same siblings — the same family. So Sally and her sisters are the sisters of each brother. We know Sally is one sister.

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

    Gemini 3.7 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How does a penguin build its house? Igloos it together. Why did the bicycle fall over? Because it was two-tired.

    Qwen3 Coder Next: Sure! Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. I told my wife she was drawing her eyebrows too high. She looked surprised. Why do bees have sticky hair?

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

    Gemini 3.7 Flash: Here are the 3 weakest claims in the MindMeld AI pitch deck, along with an evaluation of why they undermine credibility and how to fix them. The Technical Feasibility Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.

    Qwen3 Coder Next: Here are the 3 weakest claims in the MindMeld AI pitch deck, with evidence-based critique and actionable strengthening suggestions: 1. Weak Claim: “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.”

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Game

Gemini 3.7 FlashGemini 3.7 Flash

Blade Runner

1982

OK Computer

Radiohead

Frankenstein; or, The Modern Prometheus

Mary Shelley

Tokyo

Japan

Portal 2

Shooter, Puzzle

Qwen3 Coder NextQwen3 Coder Next

The Shawshank Redemption

1994

OK Computer

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Gemini 3.7 Flash has the edge: newer, bigger context window, major provider backing.

Gemini 3.7 Flash and Qwen3 Coder Next compared across 53 shared prompts
SpecGemini 3.7 FlashQwen3 Coder Next
Input price$0.375/M tokens$0.2/M tokens
Output price$1.875/M tokens$1.5/M tokens
Context window1.0M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Feb 2026
At 10M a month$3.75$3.75$2.00$2.00
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
Gemini 3.7 Flash2 hosts
HostInOutContextUptime
  • Google Vertex AI$0.38 in·$1.88 out·1M·97.9% up
  • Google AI Studio$0.75 in·$3.75 out·1M·100% up
Qwen3 Coder Next1 host
HostInOutContextUptime
  • PParasailbf16$0.12 in·$0.80 out·262k·100% up

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

Common questions

What is the difference between Gemini 3.7 Flash and Qwen3 Coder Next?

Gemini 3.7 Flash is developed by Google AI while Qwen3 Coder Next is developed by Qwen. Gemini 3.7 Flash has a 1.0M token context window vs Qwen3 Coder Next's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Gemini 3.7 Flash or Qwen3 Coder Next?

It depends on your use case. Gemini 3.7 Flash and Qwen3 Coder Next 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 Gemini 3.7 Flash cost compared to Qwen3 Coder Next?

Gemini 3.7 Flash costs $0.375/M input tokens and Qwen3 Coder Next costs $0.2/M input tokens. Qwen3 Coder Next is $0.17/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 Gemini 3.7 Flash and Qwen3 Coder Next on Rival?

This page shows a side-by-side comparison of Gemini 3.7 Flash and Qwen3 Coder Next 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

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Same lab, same size, long tail

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Model pages

  • Gemini 3.7 Flash58 outputs, specs and price
  • Qwen3 Coder Next53 outputs, specs and price
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