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  1. Home/
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  3. GPT-5.4 Pro vs Qwen3 30B A3B Instruct 2507
Updated Mar 2026

GPT-5.4 Pro vs Qwen3 30B A3B Instruct 2507

Qwen3 30B A3B Instruct 2507 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 30B A3B Instruct 2507

Which answer wins?

Written rounds

12 prompts
  • 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 30B A3B Instruct 2507: 1) Year-by-Year Financial Projections (FY2026–FY2030) Key Inputs at Close (FY2025): Revenue: $900M EBITDA: $120M Purchase Price: 12.0x EBITDA → EV = $1.44B Transaction Fees: 2.0% × $1.44B = $28.8M (equity-funded) Total Leverage: 5.5x EBITDA → Debt = $660M Term Loan: 4.0x → $480M Mezzanine: 1.5x → $180M Equity Required…

    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 30B A3B Instruct 2507: If the transistor had been invented in 1920 instead of 1947, the ripple effects would be profound—reshaping technology, war, geopolitics, and society by 1980. This alternate history would not merely accelerate existing trends, but fundamentally reconstruct the trajectory of modern civilization.

    Every model's answer to this prompt
  • 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 30B A3B Instruct 2507: Dish Name: Sunny Sauté Skillet Ingredients (7 pantry staples): Olive oil Garlic (fresh, minced) Dried spaghetti (or any short pasta) Canned crushed tomatoes Dried oregano Salt & black pepper Grated Parmesan cheese Instructions: Prep (5 mins): Bring a pot of salted water to a boil.

    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 30B A3B Instruct 2507: Your real-time collaborative document editor architecture is well-structured for a scalable, low-latency system — but it contains several critical failure modes, race conditions, and scaling bottlenecks that could degrade user experience or cause data loss.

    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 30B A3B Instruct 2507: The provided Software Consulting Agreement contains several clauses that are heavily one-sided in favor of the Client and could significantly disadvantage the Contractor, potentially rendering the agreement unenforceable or exploitative under contract law, fairness principles, and standard industry practices.

    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 30B A3B Instruct 2507: Dish Name: Echoes of the Deep: Black Coral Caviar & Algae-Infused White Sturgeon with Fermented Sea Moss Gel and Crisped Kombu Crust Conceptual Narrative: This dish is a poetic meditation on the ocean’s hidden symphony—its silence, its depth, and its forgotten rhythms.

    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 30B A3B Instruct 2507: Here are the three weakest claims in the MindMeld AI pitch deck, along with detailed explanations of why they’re problematic and concrete suggestions for strengthening them: 1. Weak Claim: "We use 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 30B A3B Instruct 2507: 1. To the experienced software engineer (distributed systems, APIs, skeptical of "next word" claims): You’re right to be skeptical—on the surface, “predict the next word” does sound like a glorified autocomplete.

    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 30B A3B Instruct 2507: 3-Month Cutting-Edge Longevity & Performance Optimization Plan for the Biohacker Designed for Peak Biological Age Reversal, Cognitive Excellence, Physical Resilience, and Stress Mastery 🎯 OVERVIEW: THE 3-MONTH LONGEVITY TRIUMVIRATE This plan integrates epigenetic modulation, mitochondrial rejuvenation, neuroplasticity…

    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 30B A3B Instruct 2507: INTERNAL INVESTMENT COMMITTEE MEMO Date: April 5, 2025 Subject: LedgerLift (LLLT) – Long Recommendation 12-Month PT: $62–$78 DCF-Driven Upside on Operational Leverage & Retention Strength 1.

    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 30B A3B Instruct 2507: CEO Action Plan: Immediate Response to Serious Undisclosed Safety Risk (48-Hour Timeline) Drug: Chronic Pain Therapeutic (Top-Selling, $2B/year, 4M patients) Issue: Previously Undetected Liver Failure Risk (1 in 8,000 over 5 years), missed in trials, not in labeling Core Principles Driving Decisions: Patient safety is…

    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 30B A3B Instruct 2507: Here’s a simple, realistic 1-month plan focused on three foundational pillars of health and longevity: Nutrition, Movement, and Sleep. Each area includes beginner-friendly, actionable steps that build sustainable habits without overwhelming beginners. Month-Long Health & Longevity Plan (3 Key Areas) 1.

    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 30B A3B Instruct 2507Qwen3 30B A3B Instruct 2507

The Shawshank Redemption

1994

OK Computer

Radiohead

Pride and Prejudice

Jane Austen

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.4 Pro has the edge: bigger model tier, newer, bigger context window, major provider backing. Qwen3 30B A3B Instruct 2507 costs 225x less per token.

GPT-5.4 Pro and Qwen3 30B A3B Instruct 2507 compared across 18 shared prompts
SpecGPT-5.4 ProQwen3 30B A3B Instruct 2507
Input price$30/M tokens$0.2/M tokens
Output price$180/M tokens$0.8/M tokens
Context window1.1M tokens131K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedMar 2026Jul 2025
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 it5 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–not listed
Qwen3 30B A3B Instruct 25073 hosts
HostInOutContextUptime
  • DDekaLLM$0.09 in·$0.30 out·262k·99.4% up
  • SSiliconFlowfp8$0.09 in·$0.30 out·262k·99.8% up
  • NNebiusfp8$0.10 in·$0.30 out·262k·91.9% up

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

Common questions

What is the difference between GPT-5.4 Pro and Qwen3 30B A3B Instruct 2507?

GPT-5.4 Pro is developed by OpenAI while Qwen3 30B A3B Instruct 2507 is developed by Qwen. GPT-5.4 Pro has a 1.1M token context window vs Qwen3 30B A3B Instruct 2507's 131K. 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 30B A3B Instruct 2507?

It depends on your use case. GPT-5.4 Pro and Qwen3 30B A3B Instruct 2507 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 30B A3B Instruct 2507?

GPT-5.4 Pro costs $30/M input tokens and Qwen3 30B A3B Instruct 2507 costs $0.2/M input tokens. Qwen3 30B A3B Instruct 2507 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 30B A3B Instruct 2507 on Rival?

This page shows a side-by-side comparison of GPT-5.4 Pro and Qwen3 30B A3B Instruct 2507 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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Same lab, same size, long tail

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Model pages

  • GPT-5.4 Pro18 outputs, specs and price
  • Qwen3 30B A3B Instruct 250759 outputs, specs and price
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