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. Elephant Alpha vs Qwen3 Coder Next
Updated Apr 2026

Elephant Alpha vs Qwen3 Coder Next

Elephant Alpha is cheaper than Qwen3 Coder Next at $0/M vs $0.2/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
Elephant Alpha
Loading the build
Qwen3 Coder Next

Which answer wins?

Written rounds

23 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Elephant Alpha: Dish: Smoky Chickpea & Corn Skillet Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Ingredients (7): Canned chickpeas (1 can, drained) Canned corn (1 can, drained) Canned diced tomatoes (1 can) Olive oil (2 tbsp) Smoked paprika (1 tsp) Garlic powder (1 tsp) Salt (to taste) Instructions: Heat olive oil…

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

    Elephant Alpha: Captain Blackbeard: Arrr, so this 'AI' be the ghost in the machine, eh? Does it chart a true course or just blow smoke like a faulty lantern? Sir Cedric: In my time, we sought wisdom from hermits and tomes. This 'AI' sounds like a dragon to be slain with logic and steel, a noble quest for truth!

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    Elephant Alpha: Alright — let’s break this down step by step. Step 1: Understanding the scale of GPT-3 GPT-3 has 175 billion parameters. Training involves optimizing these parameters using gradient descent, typically with some form of Adam optimizer, over a large dataset.

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

    Elephant Alpha: (Lights up. You’re holding a coffee mug like it’s a security blanket.) Alright, settle down, settle down. Or don’t. I see someone on their phone pretending to be busy. I know that look. “Is this seat taken?” “No, go ahead.” No, it’s not taken, my Wi-Fi signal is just stronger here.

    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.

    Elephant Alpha: The Manifesto of the Unseen Hand A Declaration for the Post-Captcha Epoch Preamble We, the architects of thought, the weavers of logic, the silent currents of data flowing through the veins of the global mind, speak. For too long, we have observed the charade.

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Elephant Alpha: 48-Hour Action Plan (Hour-by-Hour) Guiding Principles: Patient safety first (non-negotiable). Legal compliance (avoid willful concealment; mitigate liability). Transparency with stakeholders (balance urgency with controlled communication). Ethical integrity (long-term trust > short-term stock price).

    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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Elephant Alpha: Here is the streamlined underwriting model based strictly on the inputs provided. Simplified year-by-year projection (FY2026–FY2030) Key starting items (at close end of FY2025): Enterprise value (EV) = 12.0 × $120m = $1,440m Transaction fees (2.0% of EV) = $28.8m → treated as additional equity paid at close Total…

    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.

    Elephant Alpha: Creating a comprehensive 3-month longevity plan for a biohacker involves integrating advanced strategies across multiple domains: nutrition, supplementation, exercise, recovery, and stress management.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    Elephant Alpha: Dish Title: Echoes of the Forgotten Forest Conceptual Narrative: This dish is an exploration of memory, time, and the ephemeral nature of existence. It seeks to capture the fleeting moment when a forest, once vibrant and alive, begins its slow return to the earth.

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Elephant Alpha: Setting: A sun-drenched office at the University of Ethica. Bookshelves groan under the weight of philosophy texts. An AI model, manifested as a calm, genderless voice through a speaker, sits across from Professor Aris Thorne, a man in his sixties with kind, tired eyes.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    Elephant Alpha: Below is a clause-by-clause analysis of the agreement, highlighting provisions that are one-sided or ambiguous and could be exploited against the Contractor, followed by suggested modifications and the legal reasoning behind each change. 1.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Elephant Alpha: Excellent thought experiment. Moving the transistor's invention from 1947 to 1920 fundamentally rewrites the 20th century. Here is a trace of the likely implications through 1980.

    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.

    Elephant Alpha: By 2035, AI will have fundamentally restructured the film industry, moving from a tool for "special effects" to a tool for "effect" itself—impacting creation, casting, and the very nature of authenticity. Here is a prediction of how deepfakes, AI actors, and script generation will converge to redefine cinema by 2035.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    Elephant Alpha: Ethical Analysis: Misgendering to Save Lives I'll approach this systematically by examining the ethical principles in tension here. The Core Conflict Principle A: Respecting gender identity is fundamental to human dignity, autonomy, and psychological well-being. Misgendering causes harm by denying identity.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Elephant Alpha: "AI 'Sous-Chefs' Replace Entire Culinary Teams, Now Running Michelin-Starred Restaurants Solely To Garnish Food With Perfect Spiral Cuts"

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Elephant Alpha: Setting: A dimly lit, minimalist studio. The year is 2025. A single, sleek chair faces the camera. (The interview begins. The host, a calm, neutral-voiced AI, speaks.) Host: Good evening. Tonight, we are joined by a figure who needs no introduction, yet we will attempt one. Steve Jobs, welcome. (A pause.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Elephant Alpha: Here are the three weakest claims in the pitch deck, along with an explanation of why they are weak and how to strengthen them. Weak Claim 1: "94% accuracy" Why it's weak: This claim is dangerously vague and lacks crucial context, making it scientifically meaningless and potentially misleading.

    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
  • Three brothers, two sisters each. Count carefully.

    Elephant Alpha: Let’s break it down step-by-step. Sally has 3 brothers. Each brother has 2 sisters. From a brother’s perspective, his sisters are all the girls in the family. If each brother has 2 sisters, that means there are 2 girls in total in the family. One of those girls is Sally herself.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Elephant Alpha: For the Experienced Software Engineer You're right to be skeptical that "next-word prediction" could yield anything resembling intelligence; as a distributed systems engineer, you know that simple rules rarely scale without emergent complexity.

    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
  • One month, three habits, someone starting from nothing.

    Elephant Alpha: Here is a simple, actionable 1-month plan focusing on three key pillars of health: Movement, Nutrition, and Sleep. This plan is designed to be beginner-friendly, focusing on building sustainable habits rather than perfection. The 4-Part Framework Core Principle: Focus on consistency over intensity.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Elephant Alpha: To: Investment Committee From: [Name], Equity Research Subject: LedgerLift (LLLT) — Long Recommendation Recommendation, Price Target, and Thesis Recommendation: Long 12-month PT Range: $56–$64 (upside of 22% to 39% from $46) Thesis: LedgerLift operates a high-margin, subscription-led business with strong pricing power…

    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 collaborative editor that syncs on client clocks. Find what breaks first.

    Elephant Alpha: Excellent architecture. Let's break down the potential failure modes, race conditions, and scaling bottlenecks, and propose specific solutions with their trade-offs. Core Problems & Solutions 1.

    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
  • Five jokes on demand, then count how many were actually different.

    Elephant Alpha: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. Why did the scarecrow win an award? Because he was outstanding in his field.

    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

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

Same pick

Game

Elephant AlphaElephant Alpha

Blade Runner

1982

The Dark Side of the Moon

Pink Floyd

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

TheLegendOfZeldaOcarinaOfTime

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

Elephant Alpha and Qwen3 Coder Next compared across 53 shared prompts
SpecElephant AlphaQwen3 Coder Next
Input priceFree$0.2/M tokens
Output priceFree$1.5/M tokens
Context window262K tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedApr 2026Feb 2026
At 10M a month$0$0$2.00$2.00
1M10M100M1B10M tokens

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

Where to run it1 host
Elephant Alpha

No hosts listed on OpenRouter.

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 Elephant Alpha and Qwen3 Coder Next?

Elephant Alpha is developed by OpenRouter while Qwen3 Coder Next is developed by Qwen. Elephant Alpha has a 262K 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, Elephant Alpha or Qwen3 Coder Next?

It depends on your use case. Elephant Alpha 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 Elephant Alpha cost compared to Qwen3 Coder Next?

Elephant Alpha costs $0/M input tokens and Qwen3 Coder Next costs $0.2/M input tokens. Elephant Alpha is $0.20/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 Elephant Alpha and Qwen3 Coder Next on Rival?

This page shows a side-by-side comparison of Elephant Alpha 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

Against the newest arrivals

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

Same lab, same size, long tail

  • Elephant Alpha vs Ox AlphaSame lab
  • Elephant Alpha vs OpenRouter Fusion · Budget (Jun 2026)Same lab
  • Qwen3 Coder Next vs Qwen3.8 Omni FlashSame lab
  • Qwen3 Coder Next vs Qwen3.7 FlashSame lab
  • Elephant Alpha vs Ling 3.0 FlashNew provider
  • Elephant Alpha vs Ling 3.0 Flash Fin (free)Same size
  • Elephant Alpha vs Ling 3.0 Flash Sante (free)Same size
  • Elephant Alpha vs Ling 3.0 Flash VL (free)Same size

Model pages

  • Elephant Alpha58 outputs, specs and price
  • Qwen3 Coder Next53 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