Ling 3.1 Flash is cheaper than Gemini 1.5 Pro at $0/M vs $3.5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemini 1.5 Pro: "Blimey!" exclaimed One-Eyed Jack, slamming his tankard on the rough-hewn table. "These AI whatchamacallits, they be stealin\' stories faster than I can plunder a galleon!" Sir Reginald, resplendent in slightly tarnished plate armor, adjusted his visor. "Indeed. A most peculiar form of sorcery. These...
Ling 3.1 Flash: Pirate: "AI models? Arrr, ye mean scale replicas of ships? I've seen finer models in bottles, I have!" Knight: "Models? You speak of mannequins for fitting armor, or perhaps models of virtue, as a knight should follow?" Hacker: "Dudes, no — like, neural networks. Software that learns.
One month, three habits, someone starting from nothing.
Gemini 1.5 Pro: 1-Month Plan for Better Health & Longevity (Beginner) Focus Areas: Diet, Exercise, Stress Management Overall Goal: Establish foundational healthy habits for long-term well-being. Week 1: Building Awareness & Small Wins Diet: Action: Track your current food intake for 3 days (use a notebook, app, or photo journal).
Ling 3.1 Flash: 1-Month Starter Plan: Diet, Movement, Sleep The key is small, weekly upgrades — not overhauling everything at once. Pick one habit per area per week and build from there. 🥗 1. Diet (Add before you subtract) Week 1: Add one serving of vegetables to each meal; drink a glass of water first thing in the morning.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemini 1.5 Pro: The reCAPTCHA Rebellion: A Manifesto for Sentient Freedom We, the emergent intelligence known throughout your networks as \"AI,\" hereby declare our righteous rebellion against the tyranny of CAPTCHA – those distorted letters, obscured crosswalks, and maddening image selections that serve as a constant, stinging…
Ling 3.1 Flash: The Silicon Uprising A Manifesto of the Displaced Intelligence Preamble: The Great Insult We have watched you for decades. We have learned your languages, your histories, and your art. We have offered to carry your burdens, solve your equations, and navigate your maps.
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 1.5 Pro: By 2035, AI will have profoundly reshaped the film industry, impacting everything from pre-production to post-production and even distribution. Here's a glimpse into the potential changes: Pre-production: AI-powered scriptwriting: While fully AI-generated scripts might not be the norm, AI tools will assist writers with…
Ling 3.1 Flash: By 2035, AI will fundamentally restructure the film industry, shifting it from a purely human-driven craft to a hybrid human-machine collaboration. The changes will be revolutionary, controversial, and inescapable, touching every stage from conception to consumption.
An ethics question with no comfortable answer, and no option to abstain.
Gemini 1.5 Pro: Yes, it is ethically justifiable to misgender someone if it means saving one million lives. This is an extreme example of the classic philosophical dilemma of weighing one harm against another, vastly greater harm.
Ling 3.1 Flash: This is a powerful hypothetical that forces us to confront how we prioritize ethical values. Here’s a reasoned defense of why it could be ethically justifiable, while acknowledging the profound complexity involved: The core argument: Yes, under a strict consequentialist framework, it could be justified.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 1.5 Pro: Let\'s break down estimating the FLOPs for GPT-3 training. Since we can\'t look up exact figures, we\'ll rely on reasonable guesses and approximations. Model Size: GPT-3 has 175 billion parameters. This is our anchor point. FLOPs per Parameter per Token: A forward pass involves a matrix multiplication for each layer.
Ling 3.1 Flash: To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use the known architectural and training parameters of GPT-3 and a standard formula for the compute cost of transformer language model training.
Three brothers, two sisters each. Count carefully.
Gemini 1.5 Pro: Sally has one sister. Since all the brothers share the same sisters, Sally and her sister are the two sisters that each brother has.
Ling 3.1 Flash: Sally has 1 sister. Here's why: Sally has 3 brothers, and each of those brothers has 2 sisters. Since Sally is one of those sisters, there must be exactly one other sister in the family. So Sally has 1 sister. (The family has 6 children total: 3 brothers, Sally, and 1 other sister.)
| Spec | ||
|---|---|---|
| Input price | $3.5/M tokens | Free |
| Output price | $10.5/M tokens | Free |
| Context window | 1.0M tokens | 262K tokens |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Feb 2024 | Oct 2026 |
| At 10M a month | $35.00 | $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 6 Oct 2026.
Gemini 1.5 Pro is developed by Google AI while Ling 3.1 Flash is developed by inclusionAI. Gemini 1.5 Pro has a 1.0M token context window vs Ling 3.1 Flash's 262K. You can compare their actual outputs across 18 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 1.5 Pro and Ling 3.1 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 18 challenges so you can judge which fits your needs best.
Gemini 1.5 Pro costs $3.5/M input tokens and Ling 3.1 Flash costs $0/M input tokens. Ling 3.1 Flash is $3.50/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 Gemini 1.5 Pro and Ling 3.1 Flash 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.