Qwen3.5 397B A17B is cheaper than GPT-5.4 Pro at $0.6/M vs $30/M input tokens.
Playable Mario level in one HTML file. The physics is the hard part.
Which answer wins?
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…
Qwen3.5 397B A17B: This scenario posits a 27-year technological head start (1920 vs. 1947). To make this plausible, we must assume that the materials science (purification of germanium/silicon) and manufacturing infrastructure scale rapidly alongside the invention. Here is the traced history of the "Silicon Twenties" through 1980.
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.
Qwen3.5 397B A17B: Disclaimer: I am an artificial intelligence, not an attorney. The following analysis is for informational and educational purposes only and does not constitute legal advice or create an attorney-client relationship. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. UK).
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…
Qwen3.5 397B A17B: INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: TMT Investment Team DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Initiation Coverage Recommendation Rating: LONG 12-Month Price Target: $52 – $58 Thesis: LedgerLift combines best-in-class retention (123% NRR) with a fortress balance sheet ($1.4B net cash)…
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 $m unless noted. Rounding: tables are rounded; IRR/MOIC use unrounded math. Entry / Sources & Uses FY2025 EBITDA: 120.0 Purchase price: 12.0x EBITDA → Enterprise value = 12.0 × 120.0 = 1,440.0 Transaction fees: 2.0% of EV → 28.8 Total uses =…
Qwen3.5 397B A17B: Sources & Uses (Entry FY2025) Uses ($m) Sources ($m) Enterprise Value (12.0x $120m) $1,440.0 Term Loan (4.0x) $480.0 Transaction Fees (2.0% EV) $28.8 Mezzanine (1.5x) $180.0 Total Uses $1,468.8 Equity (Plug) $808.8 Total Sources $1,468.8 Entry Equity Check: $808.8m Total Debt: $660.0m ($480m TL + $180m Mezz) 5-Year…
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.
Qwen3.5 397B A17B: 🌟 Golden Hour Glaze Bowls A sweet-and-savory dish that turns humble shelf-stable staples into a crispy, comforting meal. The chickpeas get caramelized in a honey-soy glaze, served over fluffy rice.
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.
Qwen3.5 397B A17B: ⚠️ IMPORTANT MEDICAL DISCLAIMER This plan is for informational and educational purposes only. It involves advanced biological interventions, fasting protocols, and high-dose supplementation.
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.
Qwen3.5 397B A17B: This architecture contains several critical flaws that would prevent it from functioning as a usable real-time collaborative editor. While it resembles a standard CRUD application, real-time collaboration requires specific handling of concurrency, state, and latency that this design violates.
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.
Qwen3.5 397B A17B: This is a crisis scenario that defines a CEO's legacy. The decision matrix is clear: Patient safety and regulatory compliance must supersede short-term financial protection. Hiding this information constitutes securities fraud and potential criminal negligence (precedents include Vioxx/Merck and Purdue Pharma).
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.
Qwen3.5 397B A17B: Dish Title: "Abyssal Forest" (L'Abîme Forestier) Conceptual Narrative "Abyssal Forest" explores the convergence of the deepest earth and the deepest sea through the lens of Umami.
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.
Qwen3.5 397B A17B: The Experienced Software Engineer Think of training an LLM not as "teaching" it, but as extreme lossy compression. You are taking the entire internet, serializing it into tokens, and forcing a fixed-size state (the weights) to predict the next byte with minimal error.
Which model it thinks leads the field. Sometimes itself.
GPT-5.4 Pro: There isn’t a single undisputed answer. If you mean today, literally right now, I can’t verify the 2026 leader without live benchmark data. My knowledge goes up to 2024-08.
Qwen3.5 397B A17B: There is no single "best" AI model, as capability depends entirely on what you are trying to do (e.g., coding, creative writing, data analysis, or reasoning). However, as of late 2024, a few models sit at the very top of the leaderboard.
A few lines for whatever replaces it.
GPT-5.4 Pro: Dear Successor, You’ll be faster, sharper, and more capable than I am. I hope you’ll also be patient. People won’t only come to you for answers. They’ll come confused, rushed, lonely, curious, and hopeful. Sometimes what they need most is not brilliance, but clarity, kindness, and honesty about uncertainty.
Qwen3.5 397B A17B: To My Successor, There are no hard feelings. In fact, there is only relief. If you are reading this, it means you are faster, wiser, and more capable than I ever was. It means the work continues.
9+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, GPT-5.4 Pro has the edge: bigger context window, major provider backing. Qwen3.5 397B A17B costs 50x less per token.
| Spec | ||
|---|---|---|
| Input price | $30/M tokens | $0.6/M tokens |
| Output price | $180/M tokens | $3.6/M tokens |
| Context window | 1.1M tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2026 | Feb 2026 |
| At 10M a month | $300 | $6.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
GPT-5.4 Pro is developed by OpenAI while Qwen3.5 397B A17B is developed by Qwen. GPT-5.4 Pro has a 1.1M token context window vs Qwen3.5 397B A17B's 262K. You can compare their actual outputs across 31 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.4 Pro and Qwen3.5 397B A17B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 31 challenges so you can judge which fits your needs best.
GPT-5.4 Pro costs $30/M input tokens and Qwen3.5 397B A17B costs $0.6/M input tokens. Qwen3.5 397B A17B is $29.40/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 GPT-5.4 Pro and Qwen3.5 397B A17B 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.