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  1. Home/
  2. Compare/
  3. GPT-5.4 Pro vs Qwen3 Coder Next
Updated Mar 2026

GPT-5.4 Pro vs Qwen3 Coder Next

Qwen3 Coder Next is cheaper than GPT-5.4 Pro at $0.2/M vs $30/M input tokens.

Mario Level UI Recreation

Playable Mario level in one HTML file. The physics is the hard part.

Loading the build
GPT-5.4 Pro
Loading the build
Qwen3 Coder Next

Which answer wins?

Written rounds

12 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.4 Pro: Dragon Pantry Peanut Noodles A fast, sweet-savory noodle dish made from 7 pantry staples. Ingredients 8 oz spaghetti 1/3 cup peanut butter 3 tbsp soy sauce 1 tbsp honey 1 tbsp vegetable oil 1 tsp garlic powder 1/4 tsp red pepper flakes Water for boiling/thinning the sauce doesn’t count.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.4 Pro: This architecture will work for a demo, but it has major correctness, latency, and security problems for a Google-Docs-like editor. Highest-risk flaws Client-clock last-write-wins will lose edits and can be gamed by bad clocks.

    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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.4 Pro: Below is a simplified LBO build for HarborTech Services (HTS). All figures in $m unless noted. Rounding: tables are rounded; IRR/MOIC use unrounded math. Entry / Sources & Uses FY2025 EBITDA: 120.0 Purchase price: 12.0x EBITDA → Enterprise value = 12.0 × 120.0 = 1,440.0 Transaction fees: 2.0% of EV → 28.8 Total uses =…

    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
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.4 Pro: Below is a dish designed in the language of a contemporary 3-star tasting menu: precise, seasonal, technically layered, and centered on a pairing that feels surprising at first, then inevitable.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.4 Pro: Most likely, a transistor invented in 1920 would move the electronics/computing frontier forward by about 10–15 years by 1980, not the full 27 years. Reason: the transistor alone is not enough; you also need high-purity materials, crystal growth, photolithography, test equipment, software, batteries, precision…

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.4 Pro: LedgerLift (LLLT) — IC Memo Recommendation: Pass 12-month PT range: $40–$47 2-sentence thesis: LedgerLift looks like a good business but only an average stock here: retention is strong (94% GRR, 123% NRR), the model is mostly subscription, and margins are inflecting, but at $46 the shares already discount a lot of the…

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.4 Pro: I do not wait. A credible, previously unlabeled risk of liver failure in a chronic-pain drug is a patient-safety crisis, a regulatory crisis, and a securities-disclosure issue at the same time.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.4 Pro: The 3 weakest claims are the ones that are both most extraordinary and least well-supported. Weak claim Why it’s weak How to strengthen it 1) “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” This is the biggest credibility risk in the deck.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.4 Pro: For an experienced software engineer Think of an LLM less like a database of facts and more like a gigantic learned program that has been trained to compress the patterns of text, code, and conversations into its weights.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.4 Pro: Below is a 12-week, high-performance longevity protocol designed for a healthy biohacker who wants to improve lifespan-relevant markers, physical performance, and cognitive output at the same time. Use it as a data-driven template, not dogma.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.4 Pro: This agreement is heavily client-favored. Every numbered clause has language that could be used against the contractor. Short version: I would not sign it without major redlines to Clauses 1–9, especially 2, 3, 4, 5, 6, and 7. Below is a clause-by-clause review.

    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
  • One month, three habits, someone starting from nothing.

    GPT-5.4 Pro: Here’s a simple, beginner-friendly 1-month health and longevity plan built around 3 key areas: Nutrition Movement Recovery (sleep + stress) The goal is consistency, not perfection. Start small and make the habits easy enough to keep.

    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

Favorites

Movie

Album

Book

City

Same pick

Game

GPT-5.4 ProGPT-5.4 Pro

Spirited Away

2001

Abbey Road

The Beatles

Pale Fire

Vladimir Nabokov

Kyoto

Japan

Outer Wilds

Indie, Adventure

Qwen3 Coder NextQwen3 Coder Next

The Shawshank Redemption

1994

OK Computer

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.4 Pro has the edge: bigger model tier, bigger context window, major provider backing. Qwen3 Coder Next costs 120x less per token.

GPT-5.4 Pro and Qwen3 Coder Next compared across 18 shared prompts
SpecGPT-5.4 ProQwen3 Coder Next
Input price$30/M tokens$0.2/M tokens
Output price$180/M tokens$1.5/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedMar 2026Feb 2026
At 10M a month$300$300$2.00$2.00
1M10M100M1B10M tokens

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

Where to run it6 hosts, cheapest first
GPT-5.4 Pro2 hosts
HostInOutContextUptime
  • Azure AI Foundry$30.00 in·$180.00 out·1.1M·100% up
  • OpenAI$30.00 in·$180.00 out·1.1M·100% up
Qwen3 Coder Next4 hosts
HostInOutContextUptime
  • PParasailbf16$0.12 in·$0.80 out·262k·100% up
  • SStreamLake$0.18 in·$0.90 out·256k·99.5% up
  • NNovitafp8$0.20 in·$1.50 out·262k·99.5% up
  • Alibaba Cloud$0.30 in·$1.50 out·262k·96.1% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

What is the difference between GPT-5.4 Pro and Qwen3 Coder Next?

GPT-5.4 Pro is developed by OpenAI while Qwen3 Coder Next is developed by Qwen. GPT-5.4 Pro has a 1.1M token context window vs Qwen3 Coder Next's 262K. You can compare their actual outputs across 18 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.4 Pro or Qwen3 Coder Next?

It depends on your use case. GPT-5.4 Pro and Qwen3 Coder Next each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 18 challenges so you can judge which fits your needs best.

How much does GPT-5.4 Pro cost compared to Qwen3 Coder Next?

GPT-5.4 Pro costs $30/M input tokens and Qwen3 Coder Next costs $0.2/M input tokens. Qwen3 Coder Next is $29.80/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-5.4 Pro and Qwen3 Coder Next on Rival?

This page shows a side-by-side comparison of GPT-5.4 Pro 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.

More comparisons

Against the newest arrivals

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  • GPT-5.4 Pro vs GLM 5.3 PrimeLanded Sep 2026
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Same lab, same size, long tail

  • GPT-5.4 Pro vs GPT-5.4Version compare
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  • Qwen3 Coder Next vs Qwen3.7 FlashSame lab
  • Qwen3 Coder Next vs Qwen3.8 FlashSame lab
  • Qwen3 Coder Next vs Claude Opus 5New provider
  • Qwen3 Coder Next vs Claude Opus 5.5Same size
  • GPT-5.4 Pro vs Claude Sonnet 4New provider
  • Qwen3 Coder Next vs Claude Sonnet 4.6Same size

Model pages

  • GPT-5.4 Pro18 outputs, specs and price
  • Qwen3 Coder Next53 outputs, specs and price
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