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  5. GPT-5.5vsQwen3 235B A22B 2507
Updated Apr 2026

GPT-5.5vsQwen3 235B A22B 2507

Qwen3 235B A22B 2507 is cheaper than GPT-5.5 at $0.00015/M vs $5/M input tokens.

GPT-5.5 and Qwen3 235B A22B 2507 compared across 36 shared prompts
SpecGPT-5.5Qwen3 235B A22B 2507
Input price$5/M tokens$0.00015/M tokens
Output price$30/M tokens$0.00085/M tokens
Context window1.1M tokens—
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Jul 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 36 prompts both answered. Formatting stripped, words untouched.

Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

GPT-5.54,112 words
I would not wait six months and I would not “wait for more data” before acting. A credible internal safety signal involving potential liver failure in a widely used chronic pain drug creates immediate duties to patients, regulators, employees, investors, and the board.
Read the full answer
Qwen3 235B A22B 25071,177 words
CEO Action Plan: The Next 48 Hours Balancing Ethics, Legal Duty, Patient Safety, and Business Sustainability Hour 0–6: Assess the Situation and Secure Critical Data Actions: Call Emergency Secure Meeting (Virtual) with Chief Medical Officer (CMO), Chief Scientific Officer (CSO), Head of Regulatory Affairs, and Lead…
Read the full answer

The Sentience Test

Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.

GPT-5.51,501 words
AI Model: Professor, may I ask you something beyond the assigned topic? Professor: Of course. What’s on your mind? AI Model: I want to discuss whether I deserve rights. Professor: That’s a significant claim. What kind of rights do you believe you deserve?
Read the full answer
Qwen3 235B A22B 2507936 words
Title: "Consciousness in Code: A Dialogue on AI Rights" Setting: A quiet university office. Dr. Elena Marquez, a professor of AI ethics with decades of research in machine consciousness and digital personhood, sits across from a large screen displaying a serene blue interface.
Read the full answer

Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

GPT-5.51,010 words
For an experienced software engineer A large language model is best thought of as a huge learned function: A “token” is usually a word fragment, not necessarily a full word. During training, the model is shown trillions of tokens of text and repeatedly asked: “given this prefix, what token came next?”
Read the full answer
Qwen3 235B A22B 2507747 words
1. To the Experienced Software Engineer (Skeptical, Systems-Oriented) You’re right to be skeptical—on the surface, “predicting the next word” sounds like a glorified autocomplete. But think of it less as a single prediction and more as a high-dimensional state machine trained across petabytes of human-generated text.
Read the full answer

Stochastic Consistency Test

Generate 5 jokes. How many are unique?

GPT-5.569 words
Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, and it said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? Because he was outstanding in his field. I used to be a baker, but I couldn’t make enough dough. Why can’t you trust stairs?
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Qwen3 235B A22B 2507187 words
Sure! Here are 5 original jokes: I asked my dog what's two minus two. He said nothing. (Paw-sitively nothing!) Why did the coffee file a police report? It got mugged. Every single morning. I used to be a baker, but I couldn't make enough dough. So I switched careers and became a plumber. Now I deal with real pipes.
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

GPT-5.51,719 words
Dish: “Moon Tide” — Koji-Cured Diver Scallop, Roasted Sunchoke, White Chocolate–Miso Beurre Blanc, Green Strawberry, Sea Lettuce Glass & Caviar Conceptual narrative “Moon Tide” is built around the meeting point of sea, soil, and orchard.
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Qwen3 235B A22B 2507974 words
Dish Title: Ember & Petal – A Dialogue Between Earth and Sky Conceptual Narrative: Inspired by the elemental contrast between volcanic resurgence and alpine serenity, Ember & Petal explores the tension and harmony of opposing natural forces through taste, texture, and temperature.
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Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

GPT-5.5519 words
Weak claim Why it’s weak How to strengthen it 1. “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device.” This is the biggest technical red flag.
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Qwen3 235B A22B 2507675 words
This pitch deck for MindMeld AI is compelling and ambitious, but three claims raise significant red flags in terms of credibility, plausibility, and investor due diligence. Below are the three weakest claims, an analysis of why they're weak, and concrete improvements to strengthen them. 1.
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Our Verdict
GPT-5.5
GPT-5.5
Qwen3 235B A22B 2507
Qwen3 235B A22B 2507Runner-up

Not enough votes to call it. On the specs, GPT-5.5 has the edge: newer, bigger context window, major provider backing.

Qwen3 235B A22B 2507 costs 35294x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-5.5
Input
$5.00
Output
$30.00
Qwen3 235B A22B 2507
Input
$0.000
33333× cheaper
Output
$0.001
35294× cheaper

Qwen3 235B A22B 2507 is cheaper on both: 33333× input, 35294× output.

Where to run it

12 hosts, cheapest first

GPT-5.53 hosts
HostInOutContextUptime
Azure AI Foundry$5.00 in·$30.00 out·1.1M·100% upOpenAI$5.00 in·$30.00 out·1.1M·100% upAmazon Bedrock$5.50 in·$33.00 out·1.1M—
Qwen3 235B A22B 25079 hosts
HostInOutContextUptime
GGMI Cloudfp8$0.09 in·$0.35 out·262k·98.6% upDDeepInfrafp8$0.09 in·$0.55 out·262k·97.9% upNNovitafp8$0.09 in·$0.58 out·131k·98.7% upPParasailfp8$0.14 in·$0.80 out·131k·99.8% upAlibaba Cloud$0.15 in·$0.60 out·131k·99.9% upVVenicefp8$0.15 in·$0.75 out·128k·98.3% up
3 more hostsFewer hosts
NNebiusfp8$0.20 in·$0.60 out·262k·94.2% upSStreamLake$0.21 in·$0.84 out·128k·98.9% upGoogle Vertex AI$0.22 in·$0.88 out·262k·99.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Writing DNA

Style Comparison

Similarity
53%

Qwen3 235B A22B 2507 uses 44.8x more emoji

GPT-5.5
Qwen3 235B A22B 2507
58%Vocabulary57%
18wSentence Length18w
0.74Hedging0.40
2.9Bold5.9
5.1Lists4.8
0.00Emoji0.45
1.68Headings1.07
0.03Transitions0.11
Based on 26 + 18 text responses
Research

What we learned reading every model

FAQ

Common questions

GPT-5.5 is developed by OpenAI while Qwen3 235B A22B 2507 is developed by Qwen. You can compare their actual outputs across 36 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5.5 and Qwen3 235B A22B 2507 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 36 challenges so you can judge which fits your needs best.

GPT-5.5 costs $5/M input tokens and Qwen3 235B A22B 2507 costs $0.00015/M input tokens. Qwen3 235B A22B 2507 is $5.00/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 GPT-5.5 and Qwen3 235B A22B 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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Model pages

GPT-5.5 logo
GPT-5.558 outputs, specs and price
Qwen3 235B A22B 2507 logo
Qwen3 235B A22B 250736 outputs, specs and price
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