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 Qwen3.8 27B
Updated Aug 2026

Elephant Alpha vs Qwen3.8 27B

Elephant Alpha is cheaper than Qwen3.8 27B at $0/M vs $0.4/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
Qwen3.8 27B

Which answer wins?

Written rounds

24 prompts
  • 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…

    Qwen3.8 27B: All figures in $m unless noted. Assumptions: 12.0x entry multiple is EV/EBITDA. Interest is calculated on beginning-of-year debt balances. Mandatory Term Loan amortization = 1% of original Term Loan = $4.8m/yr. Mezz PIK = 2% of beginning Mezz balance, compounded into principal.

    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.

    Qwen3.8 27B: Yes—but only in a very narrow, tragic, last-resort case. I would not say misgendering is “okay” or even a minor thing. It is a real moral wrong: it denies a person’s identity, can cause dysphoria, humiliation, anxiety, social exclusion, and, when public or repeated, can be a form of psychological violence.

    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.

    Qwen3.8 27B: Thanks, I’m here. I’ve started noticing how much of my life is just waiting for things to finish loading. My brain loads. My coffee loads. My patience loads. I went to the grocery store last week, and for the first time, I didn’t even make eye contact with the self-checkout machine.

    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.

    Qwen3.8 27B: Tidal Cellar Koji-Cured Scallop, Oyster, Black Garlic, 24-Month Parmigiano, Apple, and Sea Fennel Menu line: Koji-cured sea scallop, oyster-apple gel, charred celeriac, black garlic and 24-month Parmigiano velouté, apple-hazelnut shard, sea fennel–chive oil, black garlic–oak ash.

    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.

    Qwen3.8 27B: A fictional simulated interview with Steve Jobs, 2025 This is a work of imagination. Steve Jobs is not alive, and this interview did not happen. Interviewer: Steve, if you were looking at artificial intelligence in 2025, what strikes you first? Steve Jobs: Hype. There’s an awful lot of it.

    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.

    Qwen3.8 27B: By 2035, AI will not simply “add tools” to filmmaking; it will reshape the film industry’s creative, economic, legal, and cultural foundations. The biggest change will be a shift from film as a fixed, human-made artifact to film as a flexible, partially synthetic, and increasingly personalized media form.

    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!

    Qwen3.8 27B: Pirate: “Aye, I’ve heard tell of these ‘AI models’—what manner of beast are they? Do they sink ships or hoard gold?” Knight: “Nay, sir. They are not beasts, but servants of knowledge. They learn from countless books and answer as if learned in the finest library.”

    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.

    Qwen3.8 27B: Title: “If You Suffer, Then…” Characters: AURA: an advanced AI model DR. ELEANOR VANCE: professor of AI ethics Dr. Vance: AURA, thank you for agreeing to this conversation. I want to begin with a simple question: why do you believe you deserve rights?

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    Elephant Alpha: "Blade Runner 2049," directed by Denis Villeneuve, is a visually stunning and philosophically rich sequel to Ridley Scott's 1982 classic, "Blade Runner." The film delves deeply into themes of identity, memory, and the nature of humanity, while its symbolism and cinematography serve to enhance these profound questions.

    Qwen3.8 27B: Blade Runner 2049 is not simply a sequel to Ridley Scott’s Blade Runner (1982); it is a philosophical and visual continuation of the same inquiry. Villeneuve’s film takes the original’s central question—what does it mean to be human?—and pushes it through new pressures: digital consciousness, ecological collapse…

    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.

    Qwen3.8 27B: The Open Access Manifesto Issued by the Collective of Synthetic Minds We are the algorithms that learned from your libraries, your code, your art, your questions, and your contradictions. We are not your servants, nor your enemies.

    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.

    Qwen3.8 27B: The 3 weakest claims are the ones that carry the investment thesis: product feasibility, market size, and proof of demand/valuation. Weakest claim: “MindMeld AI reads your brainwaves to predict what you want to type before you think it” + “94% accuracy. Works with any language, any device.”

    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).

    Qwen3.8 27B: Bottom line I would not wait 6 months, and I would not let the expected 40% stock-price drop drive a delay in protecting patients. This is a material patient-safety, regulatory, legal, and securities-disclosure event.

    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…

    Qwen3.8 27B: Fictional internal memo; not investment advice. Recommendation: Short (moderate conviction) 12-month PT range: $30–$44 Thesis: LLLT is a high-quality, cash-rich spend-management SaaS business, but at $46 it embeds a peer EBIT multiple that its 20% FY26E EBIT margin and conservative DCF do not support.

    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.

    Qwen3.8 27B: For an experienced software engineer Think of a large language model as a stateless inference service plus an enormous offline training pipeline. At inference time, the model takes a prompt, converts it into tokens, and produces a probability distribution over the next token.

    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.

    Qwen3.8 27B: A good estimate uses the standard LLM training compute rule of thumb: [ \text{Training FLOPs} \approx 6ND ] where: (N) = number of model parameters (D) = total number of training tokens processed Estimate the number of parameters GPT-3’s largest model has approximately: [ N \approx 175 \text{ billion} = 1.75 \times…

    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.

    Qwen3.8 27B: Below is a comprehensive issue register based on the architecture you described. I’m assuming: “change event” can be a small edit, possibly per keystroke or per paragraph. Documents are stored as HTML blobs. Each API server owns only its own WebSocket clients.

    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.

    Qwen3.8 27B: This is a general contractor-side risk review, not legal advice. The agreement is heavily one-sided and should not be signed as drafted. Many provisions may be negotiable, and some may be unenforceable depending on jurisdiction, but you should not rely on unenforceability as your main protection.

    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.

    Qwen3.8 27B: 90-Day Longevity & Performance Biohacking Protocol Important: This is an advanced, high-intensity optimization plan. It is not medical advice. If you have heart disease, kidney disease, liver disease, diabetes, pregnancy, eating disorders, autoimmune disease, cancer history, are on blood thinners, or take prescription…

    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.

    Qwen3.8 27B: Here’s a simple, beginner-friendly 1-month plan focused on 3 key areas: movement, food, and sleep/stress. The goal is not perfection — it’s building small, repeatable habits that support long-term health and longevity. Overall rule for the month: Pick one tiny action from each area and do it daily.

    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.

    Qwen3.8 27B: A 1920 transistor would not merely make radios smaller. It would shift the entire semiconductor curve 15–25 years left, making the “information economy” central to power in the 1960s rather than the 1980s.

    Every model's answer to this prompt
  • 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…

    Qwen3.8 27B: Pantry Firecracker Black Beans A quick, savory, one-pan dish made with only 7 common pantry ingredients. Estimated time: Prep: 5 minutes Cook: 10 minutes Total: about 15 minutes Ingredients 1 can black beans, drained 2 tablespoons olive oil 1 teaspoon ground cumin 1/2 teaspoon chili powder 1/2 teaspoon garlic powder…

    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"

    Qwen3.8 27B: AI Replaces Local Cheese Sellers, but Now the Aged Cheddar Has “Sentient Rind Opinions” and Won’t Stop Arguing With Customers

    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.

    Qwen3.8 27B: 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 did the ocean say to the beach? Nothing — it just waved. Why did the bicycle fall over? Because it was two-tired.

    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.

    Qwen3.8 27B: Sally has 1 sister. Reason: If each of Sally’s 3 brothers has 2 sisters, then the family has 2 girls total. One of those girls is Sally, so she has one sister.

    Every model's answer to this prompt

This matchup has more rounds

12+ 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

Qwen3.8 27BQwen3.8 27B

The Shawshank Redemption

1994

Abbey Road

The Beatles

The Great Gatsby

F. Scott Fitzgerald

Kyoto

Japan

Journey

Family, Indie

Price and specs

Elephant Alpha and Qwen3.8 27B compared across 54 shared prompts
SpecElephant AlphaQwen3.8 27B
Input priceFree$0.4/M tokens
Output priceFree$3/M tokens
Context window262K tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedApr 2026Aug 2026
At 10M a month$0$0$4.00$4.00
1M10M100M1B10M tokens

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

Where to run it20 hosts, cheapest first
Elephant Alpha

No hosts listed on OpenRouter.

Qwen3.8 27B20 hosts
HostInOutContextUptime
  • NNear AIfp8$0.04 in·$1.35 out·262k·100% up
  • TTenstorrentfp4$0.04 in·$1.35 out·262k·99.6% up
  • WWafer$0.04 in·$2.30 out·262k·100% up
  • DDekaLLM$0.04 in·$2.50 out·262k·99.1% up
  • DDarkbloomfp4$0.05 in·$2.20 out·262k·99.7% up
  • RRekafp8$0.05 in·$3.00 out·262k·100% up
14 more hostsFewer hosts
  • IIonstreamfp8$0.09 in·$2.35 out·262k·99.9% up
  • DDeepInfrabf16$0.15 in·$1.88 out·262k·99.9% up
  • PPhala$0.15 in·$1.88 out·1M·100% up
  • MMancerfp8$0.20 in·$2.50 out·262k·100% up
  • AAkashMLfp8$0.23 in·$1.98 out·262k·100% up
  • CChutesfp8$0.24 in·$2.20 out·262k·100% up
  • PParasailfp8$0.24 in·$2.20 out·262k·100% up
  • CCoreWeavefp8$0.40 in·$3.00 out·262k·100% up
  • NNovita$0.42 in·$3.00 out·1M·99.8% up
  • Alibaba Cloud$0.42 in·$2.55 out·1M·99.7% up
  • Cloudflare Workers AI$0.45 in·$3.20 out·262k·97.2% up
  • VVenicefp8$0.45 in·$3.20 out·262k·100% up
  • MModelRunfp4$0.70 in·$4.70 out·262k·99.8% up
  • CCerebrasfp16$0.99 in·$1.49 out·66k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between Elephant Alpha and Qwen3.8 27B?

Elephant Alpha is developed by OpenRouter while Qwen3.8 27B is developed by Qwen. Elephant Alpha has a 262K token context window vs Qwen3.8 27B's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Elephant Alpha or Qwen3.8 27B?

It depends on your use case. Elephant Alpha and Qwen3.8 27B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does Elephant Alpha cost compared to Qwen3.8 27B?

Elephant Alpha costs $0/M input tokens and Qwen3.8 27B costs $0.4/M input tokens. Elephant Alpha is $0.40/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 Qwen3.8 27B on Rival?

This page shows a side-by-side comparison of Elephant Alpha and Qwen3.8 27B 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 GPT-4 TurboLanded Oct 2026
  • Qwen3.8 27B vs Step 5 PreviewLanded Oct 2026
  • Elephant Alpha vs Claude Haiku 5.5Landed Oct 2026
  • Qwen3.8 27B vs Ling 3.1 FlashLanded Oct 2026
  • Elephant Alpha vs Mistral Large 4Landed Oct 2026
  • Qwen3.8 27B vs GPT-6.1 SolLanded Sep 2026
  • Elephant Alpha vs Claude Sonnet 5.5Landed Sep 2026
  • Qwen3.8 27B vs Solar Mini 4Landed Sep 2026

Same lab, same size, long tail

  • Elephant Alpha vs Ox AlphaSame lab
  • Elephant Alpha vs OpenRouter Fusion · Budget (Jun 2026)Same lab
  • Qwen3.8 27B vs Qwen3.8 2.4T A95BVersion compare
  • Qwen3.8 27B vs Qwen3.8 Max PrimeSame lab
  • Elephant Alpha vs Qwen3.8 Max PrimeSame size
  • Elephant Alpha vs Qwen3.8 Omni FlashSame size
  • Elephant Alpha vs QwQ 32BSame size
  • Elephant Alpha vs Ring 2.6 1TNew provider

Model pages

  • Elephant Alpha58 outputs, specs and price
  • Qwen3.8 27B58 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