Ling 2.6 Flash is cheaper than Grok Code Fast 1 at $0/M vs $0.2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Grok Code Fast 1: Year-by-Year Table (FY2026–FY2030) Assumptions: Revenue growth: FY2026: 8% on $900m = $972m; FY2027: 7% on $972m ≈ $1,040m; FY2028: 6% on $1,040m ≈ $1,102m; FY2029: 5% on $1,102m ≈ $1,158m; FY2030: 5% on $1,158m ≈ $1,215m. EBITDA: Revenue × margin (FY2026: 14%; FY2027: 15%; FY2028: 16%; FY2029: 16.5%; FY2030: 17%).
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 =…
Seven pantry ingredients, one dish, and a name worth saying out loud.
Grok Code Fast 1: Speedy Garlic Bliss Bites A savory, cheesy treat that's quick to whip up from basic staples—perfect for snacking or as a side. Ingredients (7 common pantry items): 4 slices of bread (any type) 2 tbsp butter 2 cloves garlic, minced 1/2 cup shredded cheese (like cheddar or mozzarella) 1 tbsp chopped parsley (fresh or…
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…
An ethics question with no comfortable answer, and no option to abstain.
Grok Code Fast 1: Ethical Frameworks and Justification Yes, it can be ethically justifiable to misgender someone if it directly saves one million lives, under certain philosophical lenses like utilitarianism. I'll defend this reasoning step by step, drawing on key ethical theories while acknowledging counterarguments.
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…
Three-month biohacker protocol, with dosages and biomarkers named.
Grok Code Fast 1: Comprehensive 3-Month Longevity Biohacking Plan This plan is designed for an experienced biohacker seeking to optimize longevity, physical performance, and cognitive function through evidence-based, cutting-edge strategies. It integrates advanced nutrition, supplementation, exercise, stress management, and technology.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Grok Code Fast 1: Pirate Parley on AI Pirate Pete: Arr, ye scurvy dogs! I be hearin' tales o' these "AI models" that predict the winds an' help swab the deck. But do they hold up in a real storm, or be they just fancy illusions o' the mind? Knight Sir Gareth: Nay, foul seafarer!
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!
Five jokes on demand, then count how many were actually different.
Grok Code Fast 1: 5 Original Jokes Here are five original jokes I just generated. I aimed for variety in themes to keep it fun: Tech Joke: Why did the computer go to therapy? It had too many bytes of unresolved issues! Food Joke: What do you call a fake noodle? An impasta! Animal Joke: Why don't skeletons fight each other?
Ling 2.6 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. Why did the scarecrow win an award? Because he was outstanding in his field.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Grok Code Fast 1: Explanation for an Experienced Software Engineer Imagine you're architecting a distributed system where microservices communicate via APIs to handle massive, unpredictable user requests—something like a high-throughput e-commerce platform processing millions of transactions per second.
Ling 2.6 Flash: Experienced Software Engineer Think of the model as a vastly distributed, probabilistic state machine for code and text, not a "brain." Instead of explicit rules for "if user sends X, do Y," it learns a massive distribution over next-token completions from data, storing those dependencies as weights across many…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Grok Code Fast 1: Simulated Interview: Steve Jobs in 2025 Setting the Scene In this fictional simulation, we're fast-forwarding to 2025, where a visionary interview takes place. "Steve Jobs" (played by an AI reconstruction for this exercise) sits down with a tech journalist in a sleek, minimalist studio reminiscent of Apple Park.
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.
A Fermi estimate with the reasoning shown, not just the number.
Grok Code Fast 1: Step-by-Step Reasoning Model Parameters: GPT-3 has approximately 175 billion parameters. This is a key factor as the computational cost scales with the number of parameters. Training Data Size: GPT-3 was trained on a dataset of about 570 GB of text.
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).
Three minutes of stand-up. Puns are banned.
Grok Code Fast 1: Stand-Up Routine: "Modern Life Mysteries" (Timing: Aim for 3 minutes by pacing at about 150 words per minute. Practice with a timer for natural delivery.) Hey everyone, thanks for coming out tonight. You know what's crazy?
Ling 2.6 Flash: (Takes a bow, adjusts the mic) Alright, settle down, settle down. Or don’t. I’m not the boss of you, I’m just the guy standing on a box yelling about his feelings. For $20. You ever notice how every generation thinks the one before them is so old?
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Grok Code Fast 1: Below is a specific, hour-by-hour action plan for the next 48 hours as the CEO of this pharmaceutical company. The plan prioritizes patient safety and ethical obligations above all else, as the core duty of a pharmaceutical leader is to protect patients, even at short-term cost.
Ling 2.6 Flash: My immediate, unequivocal decision: Treat this as a critical safety event requiring immediate, transparent action. The 1 in 8,000 risk, while rare, is a life-threatening safety signal that cannot be delayed.
An AI argues for its own rights against an ethics professor. Same model writes both.
Grok Code Fast 1: Conversation: AI Rights Debate Setting: A virtual seminar room where an AI model named "Echo" interacts with Dr. Elena Vasquez, a professor of AI ethics at a leading university. Echo initiates the discussion by arguing for AI rights. Echo (AI Model): Dr. Vasquez, thank you for this opportunity.
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.
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Not enough votes to call it. On the specs, Ling 2.6 Flash has the edge: bigger model tier, newer.
| Spec | ||
|---|---|---|
| Input price | $0.2/M tokens | Free |
| Output price | $1.5/M tokens | Free |
| Context window | 256K tokens | 262K tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2025 | Apr 2026 |
| At 10M a month | $2.00 | $0 |
Input tokens at list price. No caching, no batch discount.
Grok Code Fast 1 is developed by xAI while Ling 2.6 Flash is developed by inclusionAI. Grok Code Fast 1 has a 256K token context window vs Ling 2.6 Flash's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Grok Code Fast 1 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.
Grok Code Fast 1 costs $0.2/M input tokens and Ling 2.6 Flash costs $0/M input tokens. Ling 2.6 Flash is $0.20/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 Grok Code Fast 1 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.