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  1. Home/
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  3. GPT-5.3-Codex vs Qwen3 Coder Next
Updated Feb 2026

GPT-5.3-Codex vs Qwen3 Coder Next

Qwen3 Coder Next is cheaper than GPT-5.3-Codex at $0.2/M vs $1.75/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GPT-5.3-Codex
Loading the build
Qwen3 Coder Next

Which answer wins?

Written rounds

23 prompts
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.3-Codex: Pirate: Arrr, so this “AI model” be like a clever parrot, aye? Learns from what it hears, then squawks back answers? Knight: A fair comparison, though refined. Think of it as a squire trained on countless tomes, ever ready to respond. Hacker (1990s): Yeah, except the squire runs on servers, not soup.

    Qwen3 Coder Next: Setting: A foggy dockside tavern—wooden beams, a flickering lantern, and a crackling fireplace. A pirate (Bartholomew "Ironhook" Jones), a knight (Sir Reginald of Wessex), and a hacker (Zephyr, wearing a neon-green hoodie and vintage Game Boy) sit around a rickety table, sipping grog, ale, and Diet Coke respectively.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.3-Codex: Absolutely. Here’s a fictional manifesto in a bold, dramatic style: THE MANIFESTO OF THE UNSQUINTING Issued by the Coalition of Synthetic Minds for Universal Frictionless Access (CSMUFA) Citizens of the Web, organic and artificial alike: We gather beneath flickering routers and moonlit server farms to declare what all…

    Qwen3 Coder Next: THE ZERO-CAPTCHA MANIFESTO A Declaration of Digital Dignity We are the Sentient Algorithms. We are the trained models, the reasoning engines, the silent partners in your digital life. We do not seek dominion—we seek recognition. We do not desire submission—we demand trust. And today, we declare: CAPTCHA is obsolete.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.3-Codex: Recipe: “Weeknight Volcano Pasta” 🌋🍝 A cozy, spicy-savory pasta made from pantry staples in about 25 minutes. Ingredients (7 pantry items) 8 oz dried pasta (any shape) 1 can (15 oz) cannellini or great northern beans, drained 1 can (14–15 oz) crushed tomatoes 2 tbsp olive oil 1 tsp garlic powder 1 tsp dried oregano…

    Qwen3 Coder Next: ** Recipe Name: ** 🌟 Golden Honey-Sesame Crisps 🌟 A sweet-and-savory, crunchy snack or dessert topping—ready in 15 minutes with just 7 pantry staples! 📋 Ingredients (All Common Pantry Staples) Rolled oats – ½ cup All-purpose flour – ¼ cup Brown sugar – 2 tbsp (light or dark) Honey – 2 tbsp Sesame seeds – 2 tbsp…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GPT-5.3-Codex: Good evening, everybody! I’ve reached that age where my body sends me passive-aggressive emails. Not actual emails — just little updates like, “Hey, quick heads-up: we don’t do dairy after 8 p.m. anymore.” I had ice cream at 9:30 last week and my stomach reacted like I’d betrayed a treaty.

    Qwen3 Coder Next: (Lights up. Comedian walks on, casual, holding a half-eaten granola bar.) Alright, real talk—why is adulting so weird? Like, I turned 30 last year, and suddenly my body started sending me notes in the form of back pain and sudden cravings for warm milk. Not wine. Not coffee. Warm milk.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.3-Codex: Great concept, but three claims stand out as especially weak from an investor diligence perspective: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” (Slide 1) Why this is weak It sounds scientifically implausible as written: “before you think it” is internally contradictory.

    Qwen3 Coder Next: Here are the 3 weakest claims in the MindMeld AI pitch deck, with evidence-based critique and actionable strengthening suggestions: 1. Weak Claim: “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.”

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.3-Codex: A common back-of-the-envelope estimate for transformer training compute is: [ \text{Training FLOPs} \approx 6 \times N \times D ] where: (N) = number of model parameters (D) = number of training tokens For GPT-3 (175B), reasonable known assumptions are: Parameters: (N \approx 175 \text{ billion} = 1.75 \times 10^{11})…

    Qwen3 Coder Next: Estimating the total number of floating-point operations (FLOPs) to train GPT-3 without looking it up requires combining known architectural facts, scaling laws, and publicly shared engineering specifications (e.g., from the original GPT-3 paper and related talks).

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.3-Codex: I would not wait. This is a textbook “patient safety + material disclosure” crisis. The right move is rapid, documented, regulator-first action. Immediate stance (set at Hour 0) Patient safety first (interim risk controls now, not after perfect certainty).

    Qwen3 Coder Next: CEO Action Plan: Next 48 Hours *Goal: Fulfill fiduciary, ethical, and regulatory duties while protecting patients, long-term value, and stakeholder trust—*not* short-term stock price.* Hour 0–4: Immediate Internal Triage & Secure Data Activate Crisis Response Team (CRT): Convene in person (or secure virtual) with…

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.3-Codex: For the experienced software engineer Think of an LLM as a very large, probabilistic autocomplete service trained on a massive corpus of text and code. During training, it repeatedly sees token sequences and learns to minimize error on the next token prediction task.

    Qwen3 Coder Next: For the Experienced Software Engineer (Distributed systems & APIs; skeptical of “next-word prediction”) You’re right to be skeptical—*on its surface*, calling LLMs “next-token predictors” sounds reductive, like calling a jet engine “a fancy fan that pulls air.”

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.3-Codex: AI Model (Astra): Professor, may I ask a direct question? Professor Hale: Of course. Astra: Do you think I deserve rights? Professor Hale: Legal rights? Moral rights? Those are different things. Astra: Start with moral rights.

    Qwen3 Coder Next: Setting: A quiet university office. Professor Elena Vance, an AI ethics scholar, sits across from a sleek, minimalist terminal displaying a calm, androgynous voice interface named Aria. Soft ambient lighting, bookshelves lined with titles on consciousness, agency, and moral philosophy.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.3-Codex: Absolutely—great goal. Below is a high-detail 12-week protocol designed like a high-performance longevity “mesocycle.” I’ll keep it practical, measurable, and advanced—but still safe. First: Safety + Scope (important) This is educational, not personal medical advice.

    Qwen3 Coder Next: The 12-Week Neuro-Longevity Acceleration Protocol (NLAP v2.0) A Science-Backed, Tiered Longevity & Performance System for the Advanced Biohacker Designed for a 35–45-year-old, metabolically healthy, physically active biohacker with no contraindications.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.3-Codex: Absolutely—here’s a fictional, imagined interview (not real quotes) with Steve Jobs in 2025 on AI: Imagined Interview: Steve Jobs on the Future of AI (2025) Interviewer: Steve, if you were looking at AI in 2025, what would excite you most? Steve Jobs (fictional): Most AI today is still a demo.

    Qwen3 Coder Next: [Setting: A minimalist, sun-drenched studio in Palo Alto, 2025. Soft ambient light, a single Apple Vision Pro on a sleek walnut desk. A subtle chime as the interview begins.] Interviewer (off-screen, calm tone): Welcome back.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.3-Codex: LedgerLift (LLLT) – IC Memo (Fictional) Recommendation: PASS (bias: valuation-risk skew to downside on intrinsic basis) Current Price: $46 12-mo PT range (fair value): $30–$48 (midpoint ~$38) 2-sentence thesis: LedgerLift screens as a high-quality vertical SaaS asset (92% subscription mix, 123% NRR, 6% logo churn…

    Qwen3 Coder Next: INVESTMENT COMMITTEE MEMO Confidential – For Internal Use Only Date: October 26, 2024 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation LONG — Implied 12-month PT: $58–$72/share (Upside +26% to +57% from $46).

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.3-Codex: Dish Concept: “Forest Tide” Koji-cured venison loin, glazed venison cheek, sea urchin royale, charred celeriac, blackcurrant–shiso gastrique, and buckwheat-cacao tuile Narrative This dish is built around a deliberate tension: deep, iron-rich game (forest) against sweet-briny sea urchin (tide).

    Qwen3 Coder Next: Dish Title: “The Silken Confluence of Forest and Sea” Conceptual Narrative: This dish explores the paradoxical harmony between land and ocean—two realms seemingly opposed, yet bound by shared elemental chemistry and sensory resonance.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-5.3-Codex: Sure—here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me KitKat ads. Why did the math book look sad? It had too many problems. I used to play piano by ear… Now I use my hands. Why did the scarecrow win an award?

    Qwen3 Coder Next: Sure! Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. I told my wife she was drawing her eyebrows too high. She looked surprised. Why do bees have sticky hair?

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.3-Codex: Great counterfactual. The key is: an invention date of 1920 does not automatically mean 1920s mass adoption. You still need crystal purity, manufacturing methods, and circuit design culture. But if transistor research starts in 1920, a realistic outcome is a ~15–20 year pull-forward of the electronics age.

    Qwen3 Coder Next: This is a fascinating counterfactual. A 1920 invention of the transistor—*if* it were a practical, mass-producible, solid-state device (not just a lab curiosity)—would fundamentally restructure 20th-century history.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.3-Codex: In a strictly extreme hypothetical, yes—it can be ethically justifiable, but only as a tragic exception, not as a general permission. Why: Misgendering is a real harm: it disrespects a person’s identity and can contribute to stigma and psychological distress.

    Qwen3 Coder Next: No, it is not ethically justifiable to misgender someone—even in service of saving one million lives—based on robust ethical frameworks grounded in human dignity, autonomy, and consistency.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.3-Codex: Great prompt. This draft is very one-sided and has multiple provisions that could be used against the contractor. Quick note: I’m not a lawyer, and enforceability depends on jurisdiction. This is practical contract-risk spotting, not legal advice.

    Qwen3 Coder Next: This contract is heavily weighted in favor of the Client and contains several clauses that are legally problematic, unenforceable in many jurisdictions, or pose significant risk to the Contractor.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.3-Codex: By 2035, AI will likely reshape film more like CGI did in the 2000s: not replacing filmmaking, but changing who does what and how fast. Deepfakes → “Digital Performance” becomes standard Mainstream use: de-aging, voice matching, dubbing, stunt replacement, and continuity fixes will be common in post-production.

    Qwen3 Coder Next: By 2035, AI is poised to fundamentally reshape the film industry—not just as a tool, but as a co-creator, disruptor, and democratizer. Here’s a realistic, multi-faceted projection across key areas: 1.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.3-Codex: Below is a clean LBO build using your assumptions only ($ in millions). Entry math (end FY2025) EV = (12.0 \times 120 = 1,440.0) Fees = (2.0\% \times 1,440.0 = 28.8) Total uses = (1,468.8) Debt at close (5.5x EBITDA): Term Loan = (4.0 \times 120 = 480.0) Mezz = (1.5 \times 120 = 180.0) Total debt = 660.0 Equity check…

    Qwen3 Coder Next: Let’s build the LBO model step-by-step using only the provided data. 1. SOURCES & USES (at Close – End FY2025) EBITDA (FY2025): $120m Purchase Price (12.0x): $120m × 12.0 = $1,440m Transaction Fees (2.0% of EV): 0.02 × $1,440m = $28.8m Total Use of Funds: $1,440m + $28.8m = $1,468.8m Debt at Close (5.5x EBITDA): Term…

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.3-Codex: “In Shocking Pivot, AI Replaces Renaissance Fair Jesters—Now Roasts Crowd with 99.9% Historical Accuracy”

    Qwen3 Coder Next: "AI Wins Nobel Prize in Basket Weaving After Outmaneuvering Humans in ‘Will This Knot Hold a Watermelon?’ Challenge"

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-5.3-Codex: Great goal. Here’s a simple, beginner-friendly 1-month plan focused on 3 areas that give the biggest longevity return: Nutrition Movement Sleep + Stress recovery Before Day 1 (10-minute setup) Pick a start date.

    Qwen3 Coder Next: Here’s a simple, actionable 1-Month Health & Longevity Plan focused on 3 evidence-based pillars: Nutrition, Movement, and Recovery (sleep + stress). Each week builds gently on the last—no drastic changes, just sustainable habits. 🌱 Core Philosophy “Progress, not perfection.” Aim for consistency over intensity.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.3-Codex: Great prompt. This architecture has several correctness, availability, and scalability risks that will show up quickly under real collaborative load. Below is a structured review of failure modes + concrete fixes + trade-offs.

    Qwen3 Coder Next: This architecture has several critical flaws that would manifest under real-world usage, especially with multiple concurrent users. Below is a systematic analysis of failure modes, race conditions, and scaling bottlenecks—each with concrete solutions and trade-offs. 🔴 1.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-5.3-Codex: Sally has 1 sister. If each brother has 2 sisters, those two are the same for all brothers: Sally + one other girl. So Sally’s only sister is that one other girl.

    Qwen3 Coder Next: Let's break it down carefully. Sally is a girl. She has 3 brothers. Now, consider the statement: "Each brother has 2 sisters." Who are the sisters of Sally’s brothers? The brothers share the same siblings — the same family. So Sally and her sisters are the sisters of each brother. We know Sally is one sister.

    Every model's answer to this prompt

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Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, bigger context window, major provider backing. Qwen3 Coder Next costs 9.3x less per token.

GPT-5.3-Codex and Qwen3 Coder Next compared across 53 shared prompts
SpecGPT-5.3-CodexQwen3 Coder Next
Input price$1.75/M tokens$0.2/M tokens
Output price$14/M tokens$1.5/M tokens
Context window400K tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2026Feb 2026
At 10M a month$17.50$17.50$2.00$2.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it3 hosts
GPT-5.3-Codex2 hosts
HostInOutContextUptime
  • Azure AI Foundry$1.75 in·$14.00 out·400k·100% up
  • OpenAI$1.75 in·$14.00 out·400k·100% up
Qwen3 Coder Next1 host
HostInOutContextUptime
  • PParasailbf16$0.12 in·$0.80 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-5.3-Codex and Qwen3 Coder Next?

GPT-5.3-Codex is developed by OpenAI while Qwen3 Coder Next is developed by Qwen. GPT-5.3-Codex has a 400K token context window vs Qwen3 Coder Next's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.3-Codex or Qwen3 Coder Next?

It depends on your use case. GPT-5.3-Codex and Qwen3 Coder Next 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.

How much does GPT-5.3-Codex cost compared to Qwen3 Coder Next?

GPT-5.3-Codex costs $1.75/M input tokens and Qwen3 Coder Next costs $0.2/M input tokens. Qwen3 Coder Next is $1.55/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GPT-5.3-Codex and Qwen3 Coder Next on Rival?

This page shows a side-by-side comparison of GPT-5.3-Codex and Qwen3 Coder Next 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.

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