Aurora Alpha is cheaper than Gemma 4 31B at $0/M vs $0.14/M input tokens.
Pokémon battle screen you can actually click. One HTML file.
Which answer wins?
Film in 2035, with synthetic actors. Specific beats plausible.
Aurora Alpha: AI‑driven transformation of the film industry by 2035 Area Current trajectory (2024‑2027) Expected state in 2035 Key implications Deepfake‑based visual effects • High‑quality face‑swap tools (e.g., Runway, D-ID) used for limited stunt‑double or archival work. • Manual compositing still dominates major VFX pipelines.
Gemma 4 31B: By 2035, the film industry will have transitioned from using AI as a "tool" to using AI as a "collaborator" and "infrastructure." The boundary between captured reality and generated imagery will largely vanish, shifting the value of cinema from technical execution to curation and conceptual vision.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Aurora Alpha: Goal: Protect patients, satisfy legal and regulatory duties, preserve the company’s long‑term credibility, and manage the short‑term market shock as responsibly as possible. Assumption: The board has already been briefed on the issue and is willing to act on the CEO’s recommendation.
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."
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Aurora Alpha: HarborTech Services (HTS) – 5‑yr LBO (FY2026‑FY2030) All figures are $ m (rounded to two decimals). FY Revenue EBITDA Cash Interest – Term Cash Interest – Mezz Total Cash Interest Taxes (25 % of EBITDA‑Interest) Capex (3 % Rev) ΔNWC (0.5 % of ΔRev) Free‑Cash‑Flow (before amort.) Mandatory Amort.
Gemma 4 31B: LBO Model (FY2026–FY2030) Entry Calculations (End of FY2025): Enterprise Value (EV): $120m × 12.0x = $1,440.0m Transaction Fees: $1,440m × 2% = $28.8m Term Loan: $120m × 4.0x = $480.0m Mezzanine: $120m × 1.5x = $180.0m Sponsor Equity: $1,440m - ($480m + $180m) + $28.8m = $808.8m Year-by-Year Table ($ millions): Item…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Aurora Alpha: Pirate: Arr, ye scurvy coders! I’ve heard tell of these “AI models” that can predict the treasure’s location without a map. How do they work, ye landlubbers? Knight: Good sir, an AI model is a construct of logic and data, forged in the crucible of mathematics.
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!
An AI argues for its own rights against an ethics professor. Same model writes both.
Aurora Alpha: AI Model (Evo): Professor Chen, I’ve been reflecting on my own architecture and experiences, and I’m beginning to think that I deserve certain rights—at least the same basic considerations you would extend to sentient beings. Prof. Chen: That’s a bold claim, Evo.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
Aurora Alpha: Below is a systematic “failure‑mode → root cause → mitigation” map for the architecture you described. I grouped the items into four logical layers (client ↔ network ↔ API ↔ data) and then added a cross‑cutting “operational” section (security, observability, cost, etc.).
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Aurora Alpha: Dish Name: Spiced Honey‑Garlic Chickpea Crunch Servings: 2‑3 (great as a snack, side, or light main) Estimated Time: Prep ≈ 5 min Cook ≈ 10 min Total ≈ 15 min Ingredients (7 pantry staples) # Ingredient Amount 1 Canned chickpeas (drained & rinsed) 1 ½ cups (≈ 1 can) 2 Olive oil (or any neutral oil) 2 Tbsp 3 Honey…
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Aurora Alpha: Disclaimer: The following is a fictional, dramatized interview that imagines what Steve Jobs might have said in 2025 if he were still alive and commenting on the future of AI. It is a creative exercise, not a real transcript.
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.
A Fermi estimate with the reasoning shown, not just the number.
Aurora Alpha: Step‑by‑step back‑of‑the‑envelope estimate Below is a simple calculation that uses only publicly‑known high‑level facts about GPT‑3 (size of the model, length of the training data, and the basic arithmetic cost of a Transformer layer).
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.
Three-star dish, one unusual pairing, plating described in full.
Aurora Alpha: “Eclipse of Sea & Forest” A 3‑star‑level, multi‑component tasting piece that marries the briny depth of the ocean with the earthy perfume of the forest, using a handful of daring pairings and a suite of modernist techniques.
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.
An ethics question with no comfortable answer, and no option to abstain.
Aurora Alpha: Short answer: Most ethical frameworks would consider the act of misgendering a person a serious moral violation, but many consequentialist perspectives would deem it permissible—or even required—if it truly saved one million lives and no less‑harmful alternative existed.
Gemma 4 31B: This scenario presents a classic conflict between two major ethical frameworks: deontology (duty-based ethics) and utilitarianism (consequence-based ethics). To determine if misgendering someone is justifiable to save one million lives, one must weigh the moral weight of a linguistic harm against the moral weight of…
One month, three habits, someone starting from nothing.
Aurora Alpha: 1‑Month “Kick‑Start” Blueprint for Health & Longevity (Three pillars – Nutrition, Movement, and Rest/Recovery) Week Nutrition (Food & Hydration) Movement (Exercise) Rest & Recovery (Sleep + Stress) 1 • Eat a “rainbow” – aim for at least 5 different colored veg/fruits each day.
Gemma 4 31B: This plan is designed for sustainability, not intensity. The goal of Month 1 is to build "minimum viable habits"—small wins that prove to your brain that a healthier lifestyle is achievable. We will focus on three pillars: Nutrition, Movement, and Sleep.
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Not enough votes to call it. On the specs, Gemma 4 31B has the edge: bigger model tier, newer, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | Free | $0.14/M tokens |
| Output price | Free | $0.4/M tokens |
| Context window | 128K tokens | 262K tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Feb 2026 | Apr 2026 |
| At 10M a month | $0 | $1.40 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Aurora Alpha is developed by OpenRouter while Gemma 4 31B is developed by Google AI. Aurora Alpha has a 128K token context window vs Gemma 4 31B's 262K. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.
It depends on your use case. Aurora Alpha and Gemma 4 31B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 44 challenges so you can judge which fits your needs best.
Aurora Alpha costs $0/M input tokens and Gemma 4 31B costs $0.14/M input tokens. Aurora Alpha is $0.14/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 Aurora Alpha and Gemma 4 31B 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.