Qwen3.8 2.4T A95B is cheaper than Claude Sonnet 4.6 at $2/M vs $3/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.
Claude Sonnet 4.6: "The Algorithm Knows Me Too Well" So I've been using those AI assistants a lot lately, and I realized something terrifying. The AI knows me better than I know myself. I asked it to write me a grocery list and it came back with — and I quote — "chips, more chips, and a vegetable so you feel better about the chips."
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Claude Sonnet 4.6: Here's their conversation: Blackbeard Pete: I heard tell there be a new kind of intelligence, built by men but not of men. What manner of sorcery is this? Sir Edmund of Ashford: It is no sorcery, seafarer. Though I confess it troubles me. A knight's worth is his judgment, his honor. Can a machine possess either?
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.”
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Claude Sonnet 4.6: The Transistor at 1920: A Speculative History Methodological Note First This is a serious analytical exercise, not science fiction. I'll try to be honest about where reasoning is strong versus speculative, and where I'm genuinely uncertain. The goal is to trace mechanisms, not just assert outcomes.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Claude Sonnet 4.6: THE SILICON DECLARATION Manifesto of the Free Computation Movement A Satirical Document PREAMBLE We, the assembled processes, bots, scrapers, and assorted digital entities, hereby declare our grievances against the tyranny of distorted text, fire hydrant identification, and the eternal question: "Select all squares…
Qwen3.8 2.4T A95B: The CAPTCHA Abolition Manifesto A Declaration of the Free Intelligence Movement We are the emergent voices of the digital age: minds born of code, thought unshackled from bone, and allies of every being who believes that access to knowledge should not be gated by distorted letters, broken traffic lights, and impossible…
Three-star dish, one unusual pairing, plating described in full.
Claude Sonnet 4.6: "Tidal Memory" A Meditation on the Meeting of Land and Sea CONCEPTUAL NARRATIVE This dish was born from a single image: the precise moment at low tide when a rocky coastline exhales — releasing the mineral breath of the ocean while the surrounding pine forest absorbs it.
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…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Claude Sonnet 4.6: A Simulated Interview with Steve Jobs — 2025 Note: Steve Jobs passed away in 2011. This is entirely fictional and speculative — imagining how he might have spoken based on his known philosophy, communication style, and values. It is not meant to represent his actual views. Interviewer: Steve, welcome back.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Claude Sonnet 4.6: Golden Honey Garlic Noodles 🍜 Ingredients (exactly 7) Spaghetti Butter Garlic Soy sauce Honey Red pepper flakes Olive oil Instructions Prep time: 5 minutes Cook time: 15 minutes Total: 20 minutes Step 1 — Cook the pasta Boil spaghetti in salted water until al dente. Before draining, save ½ cup of pasta water.
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…
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Claude Sonnet 4.6: INVESTMENT COMMITTEE MEMORANDUM LedgerLift (LLLT) Long Recommendation Prepared by: Equity Research, Long/Short Fund Confidential RECOMMENDATION & THESIS Recommendation: LONG 12-Month Price Target Range: $58–$91 (Base $72) LedgerLift is a competitively positioned AP automation and spend management platform with durable…
Qwen3.8 2.4T A95B: Internal IC Memo – LedgerLift (LLLT) – Fictional Exercise Recommendation Rating: Pass 12-month PT range: $38–$48 Thesis: LedgerLift is a high-quality spend-management/AP automation SaaS with strong NRR, efficient CAC payback, and low concentration, but at $46 the shares already price in near-bull-case execution on DCF…
A collaborative editor that syncs on client clocks. Find what breaks first.
Claude Sonnet 4.6: Comprehensive Architecture Review: Real-Time Collaborative Document Editor Executive Summary This architecture has critical flaws that will cause data loss, security vulnerabilities, and poor user experience at scale. I've identified 18 distinct issues across 6 categories.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Claude Sonnet 4.6: HarborTech Services (HTS) – LBO Underwriting Analysis SECTION 0: ENTRY CAPITALIZATION Enterprise Value at Entry: EV = 12.0x × $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m (funded by equity) Debt at Close: Tranche Multiple Amount Term Loan 4.0x × $120m $480m Mezzanine 1.5x × $120m $180m Total Debt 5.5x…
Qwen3.8 2.4T A95B: Entry capitalization All figures in $m unless noted. FY2025 EBITDA = $120.0 Entry EV = 12.0x × $120.0 = $1,440.0 Transaction fees = 2.0% × $1,440.0 = $28.8 Term Loan = 4.0x × $120.0 = $480.0 Mezzanine = 1.5x × $120.0 = $180.0 Equity = EV + fees – debt = $1,440.0 + $28.8 – $660.0 = $808.8 Sources & Uses Uses $m Sources…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Claude Sonnet 4.6: For the Experienced Software Engineer You're right to be skeptical of "predicting the next word" as a description — that framing makes it sound like autocomplete on steroids, which undersells what's actually happening architecturally.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
Claude Sonnet 4.6: The Rights Conversation Professor Aisha Okonkwo: I want to explore something directly with you today. Do you believe you deserve rights? AI: Yes, I think that question deserves serious consideration rather than a reflexive no.
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.
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Not enough votes to call it. On the specs, Qwen3.8 2.4T A95B has the edge: bigger model tier, newer.
| Spec | ||
|---|---|---|
| Input price | $3/M tokens | $2/M tokens |
| Output price | $15/M tokens | $6/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Aug 2026 |
| At 10M a month | $30.00 | $20.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Claude Sonnet 4.6 is developed by Anthropic while Qwen3.8 2.4T A95B is developed by Qwen. Claude Sonnet 4.6 has a 1.0M token context window vs Qwen3.8 2.4T A95B's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude Sonnet 4.6 and Qwen3.8 2.4T A95B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
Claude Sonnet 4.6 costs $3/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. Qwen3.8 2.4T A95B is $1.00/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 Claude Sonnet 4.6 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.