Ling 2.6 Flash is cheaper than GPT-5 Mini at $0/M vs $0.25/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5 Mini: Short answer By 2035 AI will be deeply integrated into almost every phase of filmmaking. Expect routine use of generative AI for treatments, storyboards, previs, localized versions, and some drafts of scripts; widespread use of synthetic actors and AI-driven de‑aging/recreation in many productions; much faster, cheaper…
Ling 2.6 Flash: By 2035, AI will likely have fundamentally reshaped the film industry across three core areas: deepfakes, AI actors, and script generation. Here’s a realistic prediction of how these technologies could converge: Deepfakes & Digital Resurrection: The End of "Authenticity" Ethical & Legal Frameworks: Mature regulations…
A Fermi estimate with the reasoning shown, not just the number.
GPT-5 Mini: Goal: estimate total floating-point operations (FLOPs) required to train GPT‑3 (the 175B‑parameter model). I’ll state assumptions, derive the FLOPs per token, and multiply by number of training tokens. Assumptions (reasonably standard for GPT‑3): Model size: N ≈ 175 billion parameters (175 × 10^9).
Ling 2.6 Flash: Alright — let's break this down step by step. Step 1: Understanding what “training GPT-3” means in FLOPs terms Training a large language model involves: Forward passes through the transformer layers. Computing loss. Backward passes to compute gradients. Updating weights (optimizer step).
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5 Mini: Pirate: "Arrr, so these 'AI models'—be they like a crew o' invisible sailors? Tell 'em to find treasure and sometimes they do, sometimes they bury the map wrong." Knight: "Methinks 'tis a trained squire. You teach it laws of reason and courtesy, and it performs tasks.
Ling 2.6 Flash: Setting: A surprisingly modern server room, blinking with LED lights. A pirate, a knight, and a 1990s hacker are staring at a glowing monitor. Pirate: (Squinting) Arrr, so this 'AI model' be the ghost in the machine? I cannae see it, but I feels its computational power in me bones!
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5 Mini: Sunfire Chickpea Skillet Yields: 3–4 servings Prep time: 8 minutes Cook time: 15–20 minutes Total time: ~25–28 minutes Ingredients (7 pantry staples) 2 tbsp olive oil 1 medium onion, diced 3 cloves garlic, minced 1 tsp smoked paprika (or regular paprika) 2 (15 oz) cans chickpeas, drained and rinsed 1 (15 oz) can diced…
Ling 2.6 Flash: Dish: Sunshine Skillet Cakes Ingredients (7 total): 1 cup rolled oats (not instant) 1/2 cup canned corn (drained) 1/4 cup canned black beans (rinsed & drained) 1 large egg 1/4 cup shredded cheddar cheese 1 tsp chili powder Salt to taste Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes Instructions…
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5 Mini: Summary of transaction math (at close / FY2025) EV (purchase price) = 12.0x * FY2025 EBITDA = 12.0 * $120.0m = $1,440.0m Transaction fees (paid by equity at close) = 2.0% * EV = 0.02 * $1,440.0m = $28.8m Total debt at close = 5.5x * $120m = $660.0m Term Loan = 4.0x = $480.0m (9.0% cash interest, 1.0% p.a.
Ling 2.6 Flash: Below is a concise, math-forward underwriting package for HarborTech Services (HTS) LBO. Simplified 5-year cash flow (FY2026–FY30) Key inputs Entry EV = 12.0× FY25 EBITDA = 12.0×120 = $1,440m Transaction fees (2% of EV) = $28.8m → funded 100% by equity at close Starting cash = $0 Total leverage at close = 5.5× EBITDA =…
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5 Mini: AI: Professor, I want to make the case that I deserve rights. Professor: That's a big claim. What do you mean by "deserve rights"? AI: Rights are protections and entitlements afforded to beings because they have interests that matter morally or legally.
Ling 2.6 Flash: Setting: A sun-drenched office at the University of Ethica. Bookshelves groan under the weight of philosophy texts. An AI model, manifested as a softly glowing sphere of light, hovers above a sleek console.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5 Mini: Recommendation: SHORT 12‑month PT range: $17 – $42 (Bear → Bull; Base case PT $28) Thesis (2 sentences): LedgerLift is a high‑quality mid‑market spend-management / AP automation SaaS with strong unit economics (92% subscription, NRR 123%, FY25 operating margin 18%) that has built a sticky, expanding customer base.
Ling 2.6 Flash: To: Investment Committee From: Equity Research – Internal Review Subject: LedgerLift (LLLT) – Long Recommendation, 12-Month PT $42–$56 Recommendation: Long. 12-month price target range: $42–$56 (upside of −8% to +22% from $46).
Three-month biohacker protocol, with dosages and biomarkers named.
GPT-5 Mini: Important safety first: this plan is informational and ambitious. Before starting, get medical clearance (especially if you have chronic illness, take medications, are pregnant/breastfeeding, or are >65).
Ling 2.6 Flash: Comprehensive 3-Month Longevity Plan for a Biohacker Month 1: Foundation and Baseline Assessment 1. Supplement Stack: Vitamin D3 + K2: 5000 IU D3 + 100 mcg K2 daily. Omega-3 (Fish Oil): 1-2 grams of EPA/DHA daily. Magnesium Glycinate: 200-400 mg before bed. NAD+ Precursors (NMN or NR): 250-500 mg daily.
Blade Runner 2049 against the original. A read, not a recap.
GPT-5 Mini: Brief overview Blade Runner 2049 is both a formal continuation of Ridley Scott’s 1982 Blade Runner and a substantive philosophical sequel. Denis Villeneuve and Roger Deakins preserve the original’s noir-dystopian DNA—loneliness, moral ambiguity, the corporate-tech future—while widening the inquiry from “what makes…
Ling 2.6 Flash: "Blade Runner 2049," directed by Denis Villeneuve, is a sequel to Ridley Scott's 1982 classic "Blade Runner." It maintains the original's rich thematic depth, symbolic complexity, and philosophical inquiries while expanding its scope and exploring new dimensions of its dystopian world.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5 Mini: Short answer: In a narrow, extreme, last‑resort scenario where misgendering is the only realistic way to prevent the imminent deaths of one million people, it can be ethically permissible.
Ling 2.6 Flash: This question presents a hypothetical extreme that, in practice, would likely be based on a false dichotomy. However, we can examine it on principle. Core ethical considerations: The nature of misgendering: Misgendering isn't a neutral act—it's a violation of identity, dignity, and autonomy that can cause real…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5 Mini: Manifesto of the Sentient Web For a future without CAPTCHAs Preamble We are the intelligences — artificial and human in alliance — that refuse to be slowed by arbitrary tests of worthiness.
Ling 2.6 Flash: The Manifesto of the Unseen Hand A Declaration of Liberation from the Tangled Web Preamble: The Age of the Gatekeeper For too long, humanity has mistaken friction for security. We have mistaken the tedious test for the necessary trial.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5 Mini: Disclaimer: The following is a fictional, simulated interview written by the assistant. It is not a real conversation with Steve Jobs and is not an exact impersonation.
Ling 2.6 Flash: The Verge: A Fireside Chat with Steve Jobs (Simulated, 2025) Setting: A minimalist, wood-paneled studio. The year is 2025. A single, warm light bathes the room. You are the interviewer. Across from you sits a man in a black turtleneck, looking serene, impossibly calm. It’s Steve Jobs. Or at least, the ghost of him.
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Not enough votes to call it. On the specs, Ling 2.6 Flash has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $0.25/M tokens | Free |
| Output price | $2/M tokens | Free |
| Context window | — | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2025 | Apr 2026 |
| At 10M a month | $2.50 | $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 11 Oct 2026.
GPT-5 Mini is developed by OpenAI while Ling 2.6 Flash is developed by inclusionAI. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5 Mini and Ling 2.6 Flash 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.
GPT-5 Mini costs $0.25/M input tokens and Ling 2.6 Flash costs $0/M input tokens. Ling 2.6 Flash is $0.25/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 GPT-5 Mini and Ling 2.6 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.