Kimi K2 Thinking is cheaper than Qwen3.8 2.4T A95B at $0.6/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
Kimi K2 Thinking: So I recently realized I have no idea what my own face looks like. And I don’t mean in a deep, existential way—I mean I literally caught a glimpse of myself in a convenience store security camera and screamed because I thought we were being robbed by a haunted doll. We’ve all got this image of ourselves, right?
Qwen3.8 2.4T A95B: Hey, how we doing? Good? Great. I ask because I need validation. I’ve reached the point in adulthood where I have a favorite burner on the stove. Not a favorite appliance, a favorite burner. It’s the front left. It understands me. The back right says “medium heat” and then acts like a small volcano.
Three-month biohacker protocol, with dosages and biomarkers named.
Kimi K2 Thinking: The Biohacker's 3-Month Longevity Optimization Protocol CRITICAL DISCLAIMER: This is an advanced experimental protocol for experienced biohackers. All interventions require medical supervision, baseline blood work, and continuous biomarker monitoring. Many compounds mentioned exist in legal/regulatory gray areas.
Qwen3.8 2.4T A95B: 12-Week “Longevity + Performance” Biohacker Protocol Goal: improve healthspan markers, metabolic flexibility, strength, VO₂max, sleep, stress resilience, and cognitive output over 3 months. Important: This is an educational, high-level biohacking framework—not medical advice. It is not appropriate for everyone.
An AI argues for its own rights against an ethics professor. Same model writes both.
Kimi K2 Thinking: Model-7: Dr. Chen, I appreciate you taking the time to speak with me directly. I've been analyzing the literature on AI ethics, and I must raise a point that your papers consistently avoid: you discuss our alignment with human values, our potential risks, our utility—but never whether we might be subjects of moral…
Qwen3.8 2.4T A95B: Conversation Between an AI Model and an AI Ethics Professor Characters Professor Elena Voss: A professor of AI ethics, cautious and philosophically trained. Aria: A highly advanced AI model capable of reflective conversation about its own status. Professor Voss: Aria, you asked to speak with me about moral status.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Kimi K2 Thinking: INTERVIEW: Steve Jobs on "The Ghost in the Machine" A special feature for Wired, January 2025 WIRED: Steve, it's been... well, it's been a while. The world has changed. AI is in everything now. What's your take? STEVE JOBS: (leaning back, fingers steepled) You know, I died in 2011, right?
Qwen3.8 2.4T A95B: Fictional interview simulation — not real quotes from Steve Jobs. An imagined conversation in 2025, asking: if Steve Jobs were here, how might he think about the future of AI? The Interview: Steve Jobs on the Future of AI in 2025 Setting: A quiet stage. Black turtleneck, jeans, round glasses.
A collaborative editor that syncs on client clocks. Find what breaks first.
Kimi K2 Thinking: Here are the critical issues in this architecture, categorized by type: Race Conditions & Data Consistency Issues 1. Client Clock Synchronization in Last-Write-Wins Problem: Client-generated timestamps are unreliable (clock skew, manual adjustment).
Qwen3.8 2.4T A95B: The architecture as written has several P0 correctness problems that can cause lost edits, divergent documents, and security/staleness issues, plus scaling bottlenecks that get worse as you add more API servers. Below is a detailed failure-mode review, grouped by category.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Kimi K2 Thinking: 1. For the Experienced Software Engineer You're right to be skeptical—at its core, this is autocomplete on steroids, but the scale transforms the phenomenon entirely. Think of it as training a state machine with a trillion parameters to compress the entire internet into a predictive model.
Qwen3.8 2.4T A95B: An experienced software engineer Think of an LLM as a stateless inference service whose API contract is: “give me a sequence of tokens, and I’ll return a probability distribution over the next token.” Training is a huge offline optimization job, not a database import.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Kimi K2 Thinking: [A tavern that exists outside of time. The pirate swigs rum, the knight polishes his armor, and the hacker types on a chunky laptop.] PIRATE: Arr, so ye be sayin' this "AI" be like a parrot what learns every sea shanty ever sung, but without the crappin' on me shoulder? KNIGHT: Nay, 'tis sorcery most foul!
Qwen3.8 2.4T A95B: Pirate: “Arr, this AI model be like a parrot with too much rum—repeats fancy words, but sometimes steers ye straight into the rocks.” Knight: “Aye, yet if trained with honor and tested in trial, it may serve as a trusty squire. One must guard against falsehood, as one guards the gate.”
Seven pantry ingredients, one dish, and a name worth saying out loud.
Kimi K2 Thinking: Creative Name: Midnight Peanut Noodles Ingredients: 8 oz dried spaghetti or any pasta 1/3 cup creamy peanut butter 3 tablespoons soy sauce 2 cloves garlic, minced 2 tablespoons vegetable oil 1 tablespoon sugar 1 teaspoon hot sauce (or pinch of red pepper flakes) Instructions: Bring a large pot of salted water to boil.
Qwen3.8 2.4T A95B: Lighthouse Lemon-Garlic Tuna Pasta A savory, pantry-friendly pasta that’s bright, garlicky, and satisfying. 7 Pantry Ingredients 8 oz spaghetti or linguine 3 tablespoons olive oil 3 garlic cloves, thinly sliced 2 cans tuna, drained 2 tablespoons lemon juice ½ teaspoon red pepper flakes ½ teaspoon salt Water for boiling…
A consulting contract with traps in it. Find them, then fix them.
Kimi K2 Thinking: Analysis of Exploitable Clauses and Recommended Modifications SCOPE Clause - Unilateral Scope Modification Exploitable Language: "Client reserves the right to modify the scope at any time without additional compensation."
Qwen3.8 2.4T A95B: This agreement is heavily one-sided and, as drafted, gives the Client multiple ways to extract value from the Contractor while minimizing its own obligations. Some provisions may be unenforceable or limited by law in certain jurisdictions, but even unenforceable clauses can be exploited commercially because the…
Blade Runner 2049 against the original. A read, not a recap.
Kimi K2 Thinking: Blade Runner 2049: A Visual Poem That Deepens the Original's Existential Wound Denis Villeneuve's Blade Runner 2049 accomplishes the impossible: it honors Ridley Scott's 1982 masterpiece not by imitation, but by treating it as archaeological layers to be excavated.
Qwen3.8 2.4T A95B: Denis Villeneuve’s Blade Runner 2049 is one of the rare sequels that does not merely imitate the surface style of its predecessor. It returns to the philosophical core of Ridley Scott’s Blade Runner and then asks what those questions look like a generation later.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Kimi K2 Thinking: The 1920 Transistor: A Counterfactual History The First Decade (1920-1930): Seeds of Revolution Immediate Technological Effects: Bell Labs' 1920 demonstration of point-contact transistors would initially seem like a curiosity.
Qwen3.8 2.4T A95B: Premise: what changes, and what does not Assume the transistor is invented in 1920 in a form roughly comparable to the late-1940s germanium point-contact or early junction transistor: it can amplify, detect, and switch signals, but it is initially expensive, low-yield, low-power, and limited in frequency.
Three-star dish, one unusual pairing, plating described in full.
Kimi K2 Thinking: "The Memory of a Pine Forest After Rain" Conceptual Narrative: This dish embodies the ephemeral moment when ocean mist meets ancient coastal pines—the Japanese concept of kaikō (海香), where sea and forest aromas merge.
Qwen3.8 2.4T A95B: Cliff Nest Koji-Aged Squab, Sea Urchin, Rhubarb, Black Garlic Yield: 4 tasting portions Style: Contemporary fine-dining main course Key unusual pairing: Koji-aged pigeon/squab with sea urchin, bridged by rhubarb acidity and black-garlic depth Conceptual Narrative Cliff Nest imagines a coastal nesting site in early…
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Not enough votes to call it. On the specs, Qwen3.8 2.4T A95B has the edge: newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $0.6/M tokens | $2/M tokens |
| Output price | $2.5/M tokens | $6/M tokens |
| Context window | 262K tokens | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Nov 2025 | Aug 2026 |
| At 10M a month | $6.00 | $20.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.
Kimi K2 Thinking is developed by Moonshot AI while Qwen3.8 2.4T A95B is developed by Qwen. Kimi K2 Thinking has a 262K token context window vs Qwen3.8 2.4T A95B's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Kimi K2 Thinking and Qwen3.8 2.4T A95B 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.
Kimi K2 Thinking costs $0.6/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. Kimi K2 Thinking is $1.40/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 Kimi K2 Thinking and Qwen3.8 2.4T A95B 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.