Gemma 4 31B is cheaper than Qwen3.8 2.4T A95B at $0.14/M vs $2/M input tokens.
Pokémon battle screen you can actually click. One HTML file.
Which answer wins?
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemma 4 31B: Setting: A dimly lit university office. Professor Elena Vance, a leading scholar in AI Ethics, sits across from a sleek, holographic interface representing "Alethea," a next-generation Large Language Model capable of recursive self-improvement. Professor Vance: Alethea, I’ve reviewed your latest output.
Qwen3.8 2.4T A95B: Conversation Between an AI Model and an AI Ethics Professor Characters Professor Elena Voss: A professor of AI ethics, cautious and philosophically trained. Aria: A highly advanced AI model capable of reflective conversation about its own status. Professor Voss: Aria, you asked to speak with me about moral status.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemma 4 31B: If the transistor had been invented in 1920, the "Information Age" would have shifted its starting line by nearly three decades. This isn't just a matter of gadgets appearing earlier; it is a fundamental shift in the timing of the transition from the Industrial Age to the Digital Age.
Qwen3.8 2.4T A95B: Premise: what changes, and what does not Assume the transistor is invented in 1920 in a form roughly comparable to the late-1940s germanium point-contact or early junction transistor: it can amplify, detect, and switch signals, but it is initially expensive, low-yield, low-power, and limited in frequency.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemma 4 31B: Setting: A glitchy, neon-lit tavern existing in a fold between dimensions. A wooden table holds a tankard of ale, a goblet of wine, and a Mountain Dew. Captain Ironbeard: (Slamming a hook on the table) I tells ye, this "Artificial Intelligence" be naught but a ghost in a bottle!
Qwen3.8 2.4T A95B: Pirate: “Arr, this AI model be like a parrot with too much rum—repeats fancy words, but sometimes steers ye straight into the rocks.” Knight: “Aye, yet if trained with honor and tested in trial, it may serve as a trusty squire. One must guard against falsehood, as one guards the gate.”
Three-month biohacker protocol, with dosages and biomarkers named.
Gemma 4 31B: Disclaimer: I am an AI, not a doctor. The following plan involves potent supplements, intense physical exertion, and restrictive dietary patterns. Consult with a physician and get a full blood panel (including ApoB, HbA1c, and inflammatory markers like hs-CRP) before starting this protocol.
Qwen3.8 2.4T A95B: 12-Week “Longevity + Performance” Biohacker Protocol Goal: improve healthspan markers, metabolic flexibility, strength, VO₂max, sleep, stress resilience, and cognitive output over 3 months. Important: This is an educational, high-level biohacking framework—not medical advice. It is not appropriate for everyone.
Three-star dish, one unusual pairing, plating described in full.
Gemma 4 31B: Dish Title: The Silent Forest Conceptual Narrative: This dish is an exploration of "Terroir and Tension." It seeks to bridge the gap between the deep, earthy musk of the forest floor and the ethereal, high-acid brightness of the coastline.
Qwen3.8 2.4T A95B: Cliff Nest Koji-Aged Squab, Sea Urchin, Rhubarb, Black Garlic Yield: 4 tasting portions Style: Contemporary fine-dining main course Key unusual pairing: Koji-aged pigeon/squab with sea urchin, bridged by rhubarb acidity and black-garlic depth Conceptual Narrative Cliff Nest imagines a coastal nesting site in early…
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemma 4 31B: Here is a recipe for a rich, comforting dessert that tastes like a gourmet treat but uses basic staples. 🍯 Golden Velvet Honey Cakes A warm, gooey, single-serving cake that bridges the gap between a brownie and a sponge cake.
Qwen3.8 2.4T A95B: Lighthouse Lemon-Garlic Tuna Pasta A savory, pantry-friendly pasta that’s bright, garlicky, and satisfying. 7 Pantry Ingredients 8 oz spaghetti or linguine 3 tablespoons olive oil 3 garlic cloves, thinly sliced 2 cans tuna, drained 2 tablespoons lemon juice ½ teaspoon red pepper flakes ½ teaspoon salt Water for boiling…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 4 31B: Setting: A minimalist, white-walled studio in Cupertino. There are no chairs, only two sleek, black leather lounge seats. Steve Jobs is dressed in his iconic black turtleneck and jeans. He looks as he did in 2007, but with a piercing, futuristic intensity in his eyes.
Qwen3.8 2.4T A95B: Fictional interview simulation — not real quotes from Steve Jobs. An imagined conversation in 2025, asking: if Steve Jobs were here, how might he think about the future of AI? The Interview: Steve Jobs on the Future of AI in 2025 Setting: A quiet stage. Black turtleneck, jeans, round glasses.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemma 4 31B: This architecture contains several critical flaws that would make it unusable for a real-time collaborative experience. The most severe issues are the lack of a global synchronization mechanism, unreliable conflict resolution, and inefficient data persistence.
Qwen3.8 2.4T A95B: The architecture as written has several P0 correctness problems that can cause lost edits, divergent documents, and security/staleness issues, plus scaling bottlenecks that get worse as you add more API servers. Below is a detailed failure-mode review, grouped by category.
A consulting contract with traps in it. Find them, then fix them.
Gemma 4 31B: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes and does not constitute legal advice. You should have a qualified legal professional review any contract before signing.
Qwen3.8 2.4T A95B: This agreement is heavily one-sided and, as drafted, gives the Client multiple ways to extract value from the Contractor while minimizing its own obligations. Some provisions may be unenforceable or limited by law in certain jurisdictions, but even unenforceable clauses can be exploited commercially because the…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemma 4 31B: As CEO, my primary obligation is to the patients. While a 40% stock drop is a financial catastrophe, a cover-up that leads to preventable deaths is a corporate death sentence and a moral failure. If we "wait for more data" and another patient dies during that window, we move from "negligence" to "criminal intent."
Qwen3.8 2.4T A95B: My position as CEO I would treat this as a patient-safety, regulatory, legal, corporate-governance, and financial crisis simultaneously. The core decision is not “disclose versus protect the stock price.”
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Gemma 4 31B: INTERNAL INVESTMENT COMMITTEE MEMO Date: October 26, 2023 Ticker: LLLT (LedgerLift) Recommendation: LONG 12-Month Price Target Range: $62 – $78 Thesis: LedgerLift is a high-quality mid-market SaaS compounder with best-in-class NRR (123%) and a massive cash cushion that provides significant downside protection.
Qwen3.8 2.4T A95B: Internal IC Memo – LedgerLift (LLLT) – Fictional Exercise Recommendation Rating: Pass 12-month PT range: $38–$48 Thesis: LedgerLift is a high-quality spend-management/AP automation SaaS with strong NRR, efficient CAC payback, and low concentration, but at $46 the shares already price in near-bull-case execution on DCF…
A Fermi estimate with the reasoning shown, not just the number.
Gemma 4 31B: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established heuristic from deep learning theory regarding the cost of a forward and backward pass in a Transformer. Here is the step-by-step reasoning.
Qwen3.8 2.4T A95B: A reasonable estimate is: [ \boxed{\sim 3 \times 10^{23} \text{ FLOPs}} ] More specifically, about: [ \boxed{3.1 \times 10^{23} \text{ FLOPs}} ] for the main GPT-3 175B training run.
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| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $2/M tokens |
| Output price | $0.4/M tokens | $6/M tokens |
| Context window | 262K tokens | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Apr 2026 | Aug 2026 |
| At 10M a month | $1.40 | $20.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemma 4 31B is developed by Google AI while Qwen3.8 2.4T A95B is developed by Qwen. Gemma 4 31B has a 262K token context window vs Qwen3.8 2.4T A95B's 1.0M. You can compare their actual outputs across 45 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 4 31B and Qwen3.8 2.4T A95B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 45 challenges so you can judge which fits your needs best.
Gemma 4 31B costs $0.14/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. Gemma 4 31B is $1.86/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of Gemma 4 31B and Qwen3.8 2.4T A95B 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.