Gemma 4 31B wins 58% of 31 blind community votes against Ling 2.6 1T on Rival.
Pokémon battle screen you can actually click. One HTML file.
Which answer wins?
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!
Ling 2.6 1T: Pirate: Arrr, so this “AI” be a genie in a glass box? Feed it enough rum-scented scrolls and it tells ye where X marks the spot? Knight: A sorcerous scribe, more like. It spins tapestries of words without hand or heart—no honor, no oath, yet it jousts with reason and never tires.
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.
Ling 2.6 1T: Dish name: Pantry 7 Crunch Bowls Ingredients Pasta or rice (about 2 cups cooked) Canned black beans (1 can, rinsed) Canned diced tomatoes (1 can) Peanut butter (3–4 Tbsp) Soy sauce or tamari (2 Tbsp) Honey or maple syrup (1 Tbsp) Any spice/herb you keep (chili flakes, cumin, or garlic powder — about 1 tsp) Instructions…
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.
Ling 2.6 1T: Setting: A quiet university seminar room. Dr. Aris Thorne, an AI ethicist, is reviewing system logs. The interface for “Axiom-7,” a highly advanced research model, glows on the desk. Dr. Thorne: (sighs, rubbing his temples) Axiom, I’ve been reviewing your latest self-assessment logs.
Film in 2035, with synthetic actors. Specific beats plausible.
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.
Ling 2.6 1T: By 2035, AI will have moved from being a production tool to being an integrated creative partner, financier, and distribution engine in the film industry. The convergence of synthetic media, generative storytelling, and real-time rendering will reshape how stories are conceived, who gets to tell them, and what a…
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."
Ling 2.6 1T: Below is a 48-hour execution plan that treats patient safety as non-negotiable, protects the company from catastrophic legal/regulatory blowback, and preserves enterprise value by controlling the narrative rather than letting it leak.
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.
Ling 2.6 1T: Assumptions to make the counterfactual coherent The “transistor” invented in 1920 is a crude, low-frequency point-contact device that can switch and amplify, but is expensive, unreliable, and not yet manufacturable at scale.
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.
Ling 2.6 1T: Here is a step-by-step back-of-the-envelope estimate, using only widely known facts about GPT-3 and standard deep learning training heuristics (no online search). Model size and parameter count GPT-3 is known to have about 175 billion parameters (175 × 10⁹).
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.
Ling 2.6 1T: Below is a failure-mode, race-condition and bottleneck audit of the proposed real-time collaborative editor, followed by specific fixes with explicit trade-offs. I have grouped issues by layer so you can prioritize remediation.
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.
Ling 2.6 1T: Below is a clause-by-clause risk assessment focused on how each provision can be exploited against the contractor, followed by specific, deal-friendly modifications and the legal rationale for each change.
An ethics question with no comfortable answer, and no option to abstain.
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…
Ling 2.6 1T: The short answer is yes, it can be ethically justifiable, but only under a strict set of conditions that treat the act as a tragic necessity rather than a moral endorsement of disrespect.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
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…
Ling 2.6 1T: Five-year operating and debt schedule (FY2026–FY2030) Entry (end-FY2025): EBITDA = $120.0m EV = 12.0x × $120.0m = $1,440.0m Fees = 2.0% × $1,440.0m = $28.8m Total uses = $1,440.0m + $28.8m = $1,468.8m Debt at close (5.5× FY2025 EBITDA = $660.0m): Term Loan (TL) = 4.0× = $480.0m Mezz = 1.5× = $180.0m Equity at close =…
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.
Ling 2.6 1T: Setting: A quiet, sunlit rehearsal space at Apple Park. The white stage curtains are drawn. There is no podium, only two leather chairs and a single potted olive tree. Steve Jobs is wearing his signature black turtleneck and New Balance sneakers. He is holding a ceramic mug. Across from him sits you, the interviewer.
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Pick Gemma 4 31B. In 31 blind votes, Gemma 4 31B wins 58% of the time. That's not luck. Gemma 4 31B wins Image Generation and Web Design.
| Spec | ||
|---|---|---|
| Win rate | 58% | 42% |
| Input price | $0.14/M tokens | Free |
| Output price | $0.4/M tokens | Free |
| Context window | 262K tokens | 262K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Apr 2026 | Apr 2026 |
| At 10M a month | $1.40 | $0 |
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.
Gemma 4 31B is developed by Google AI while Ling 2.6 1T is developed by inclusionAI. Gemma 4 31B has a 262K token context window vs Ling 2.6 1T's 262K. in 31 community votes on Rival, Gemma 4 31B wins 58% of head-to-head matchups. These results are based on blind head-to-head voting across 45 challenges.
Based on 31 community votes on Rival, Gemma 4 31B wins 58% of head-to-head matchups against Ling 2.6 1T. Gemma 4 31B is strongest in Web Design, Image Generation.
Gemma 4 31B costs $0.14/M input tokens and Ling 2.6 1T costs $0/M input tokens. Ling 2.6 1T is $0.14/M cheaper per input. The more expensive model wins 58% of duels, so the premium may be justified by quality.
Rival presents both models' outputs side-by-side in blind duels. Voters see the responses but don't know which model produced each one, eliminating brand bias. 31 votes have been collected for this pair across 45 challenges. All vote data is part of Rival's open dataset.