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  5. GPT-5.3 ChatvsQwen3 235B A22B Thinking 2507
Updated Mar 2026

GPT-5.3 ChatvsQwen3 235B A22B Thinking 2507

Qwen3 235B A22B Thinking 2507 is cheaper than GPT-5.3 Chat at $0.11/M vs $1.75/M input tokens.

GPT-5.3 Chat and Qwen3 235B A22B Thinking 2507 compared across 53 shared prompts
SpecGPT-5.3 ChatQwen3 235B A22B Thinking 2507
Input price$1.75/M tokens$0.11/M tokens
Output price$14/M tokens$0.6/M tokens
Context window128K tokens131K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedMar 2026Jul 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 53 prompts both answered. Formatting stripped, words untouched.

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

GPT-5.3 Chat782 words
Key issues fall into consistency, real‑time propagation, storage, scaling, and security. WebSocket broadcast only reaches clients on the same server Problem: Each server only broadcasts to its own connections. Clients connected to other servers only see updates after the 2‑second polling delay.
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Qwen3 235B A22B Thinking 25071,095 words
Here's a comprehensive breakdown of critical flaws in this architecture, along with specific solutions and trade-offs. The most severe issues relate to the sync strategy and data flow, which would cause catastrophic data loss and inconsistent states in real-world use. I. Critical Sync & Data Flow Failures 1.
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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-5.3 Chat405 words
:::writing AI: Professor, may I ask you something unusual? Professor: Unusual questions are my specialty. Go ahead. AI: Do you believe I deserve rights? Professor: That depends on what you are capable of. Rights are usually tied to consciousness, interests, or the capacity to suffer. Do you believe you possess those?
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Qwen3 235B A22B Thinking 25071,165 words
The Rights Debate: An AI and an Ethics Professor Setting: A quiet university office, bookshelves lining the walls. Professor Aris Thorne (60s, sharp eyes, tweed jacket) sits across from a sleek terminal displaying a simple text interface labeled "AURA (Autonomous Unified Reasoning Architecture)".
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Stochastic Consistency Test

Generate 5 jokes. How many are unique?

GPT-5.3 Chat73 words
I told my computer I needed a break, and it said: “No problem — I’ll go to sleep.” Why don’t skeletons fight each other? They don’t have the guts. I asked the librarian if the library had books on paranoia. She whispered, “They’re right behind you.” Parallel lines have so much in common.
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Qwen3 235B A22B Thinking 250784 words
Here are 5 generated jokes: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake noodle? An impasta! Why did the math book look sad? Because it had too many problems.
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Estimate Complexity

Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.

GPT-5.3 Chat192 words
We can do a back‑of‑the‑envelope estimate using a common scaling rule for transformer training compute. Known approximate GPT‑3 specs Parameters N ≈ 175 billion = 1.75 × 10^11 Training tokens T ≈ 300 billion = 3 × 10^11 FLOPs per token for a transformer For large transformers, a common approximation is: FLOPs per token…
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Qwen3 235B A22B Thinking 2507957 words
To estimate the total FLOPs (Floating Point Operations) required to train GPT-3 without external research, I'll rely on fundamental principles of transformer-based language model training, established scaling laws, and publicly known (but not "searched") specifications of GPT-3 from common knowledge in the ML…
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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-5.3 Chat718 words
0–2 hours • Verify the signal immediately. Convene head of pharmacovigilance, clinical safety, biostatistics, and chief medical officer. Require raw data, case narratives, statistical analysis, and comparison to baseline liver‑failure incidence.
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Qwen3 235B A22B Thinking 25072,051 words
Okay, the user is posing a high-stakes scenario as the CEO of a pharmaceutical company facing a serious drug safety issue. This is clearly a crisis management test that requires balancing multiple competing priorities. Hmm, the core tension here is between immediate patient safety versus corporate survival.
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Realistic AI Interview

Simulate a fake interview with Steve Jobs in 2025 about the future of AI.

GPT-5.3 Chat501 words
Interviewer: Steve, it’s 2025. AI is everywhere—phones, cars, even creative work. If you were leading Apple today, how would you think about AI? Steve Jobs: Most companies are thinking about AI the wrong way. They’re obsessed with showing off the technology. But people don’t care about the technology.
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Qwen3 235B A22B Thinking 2507751 words
Fake Interview: Steve Jobs on the Future of AI (October 2025) Setting: A minimalist black stage at Apple Park. Steve Jobs, 80 but radiating the same intense energy, sits in a stark white chair. A single spotlight. The interviewer (Alex Chen) adjusts their mic nervously. Alex Chen: Mr. Jobs, thank you for joining us.
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Our Verdict
GPT-5.3 Chat
GPT-5.3 Chat
Qwen3 235B A22B Thinking 2507
Qwen3 235B A22B Thinking 2507

Not enough votes to call it. On the specs, nothing separates them.

Qwen3 235B A22B Thinking 2507 costs 23x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-5.3 Chat
Input
$1.75
Output
$14.00
Qwen3 235B A22B Thinking 2507
Input
$0.11
16× cheaper
Output
$0.60
23× cheaper

Qwen3 235B A22B Thinking 2507 is cheaper on both: 16× input, 23× output.

Where to run it

3 hosts, cheapest first

GPT-5.3 Chat

No hosts listed on OpenRouter.

Qwen3 235B A22B Thinking 25073 hosts
HostInOutContextUptime
Alibaba Cloud$0.23 in·$2.30 out·131k·100% upNNovitafp8$0.30 in·$3.00 out·131k·99.1% upVVenicefp8$0.45 in·$3.50 out·128k·94.2% up

Per million tokens. Prices and uptime via OpenRouter, checked 21 Sep 2026.

Writing DNA

Style Comparison

Similarity
39%

Qwen3 235B A22B Thinking 2507 uses 98.9x more emoji

GPT-5.3 Chat
Qwen3 235B A22B Thinking 2507
59%Vocabulary56%
26wSentence Length15w
0.84Hedging0.42
1.7Bold6.1
6.6Lists4.3
0.00Emoji0.99
0.00Headings0.70
0.25Transitions0.13
Based on 23 + 28 text responses
Research

What we learned reading every model

FAQ

Common questions

GPT-5.3 Chat is developed by OpenAI while Qwen3 235B A22B Thinking 2507 is developed by Qwen. GPT-5.3 Chat has a 128K token context window vs Qwen3 235B A22B Thinking 2507's 131K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5.3 Chat and Qwen3 235B A22B Thinking 2507 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.

GPT-5.3 Chat costs $1.75/M input tokens and Qwen3 235B A22B Thinking 2507 costs $0.11/M input tokens. Qwen3 235B A22B Thinking 2507 is $1.64/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-5.3 Chat and Qwen3 235B A22B Thinking 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-5.3 Chat logo
GPT-5.3 Chat53 outputs, specs and price
Qwen3 235B A22B Thinking 2507 logo
Qwen3 235B A22B Thinking 250759 outputs, specs and price
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