What is the difference between GPT-5.2 Pro and Qwen3.8 Max Prime?

GPT-5.2 Pro is developed by OpenAI while Qwen3.8 Max Prime is developed by Qwen. GPT-5.2 Pro has a 400K token context window vs Qwen3.8 Max Prime's 1.0M. You can compare their actual outputs across 16 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.2 Pro or Qwen3.8 Max Prime?

It depends on your use case. GPT-5.2 Pro and Qwen3.8 Max Prime each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 16 challenges so you can judge which fits your needs best.

How much does GPT-5.2 Pro cost compared to Qwen3.8 Max Prime?

GPT-5.2 Pro costs $21/M input tokens and Qwen3.8 Max Prime costs $4/M input tokens. Qwen3.8 Max Prime is $17.00/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-5.2 Pro and Qwen3.8 Max Prime on Rival?

This page shows a side-by-side comparison of GPT-5.2 Pro and Qwen3.8 Max Prime 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.

Updated Sep 2026

GPT-5.2 ProvsQwen3.8 Max Prime

Qwen3.8 Max Prime is cheaper than GPT-5.2 Pro at $4/M vs $21/M input tokens.

GPT-5.2 Pro and Qwen3.8 Max Prime compared across 16 shared prompts
Spec	GPT-5.2 Pro	Qwen3.8 Max Prime
Input price	$21/M tokens	$4/M tokens
Output price	$168/M tokens	$12/M tokens
Context window	400K tokens	1.0M tokens
Weights	Closed	Closed
Free API (OpenRouter)	No	No
Released	Dec 2025	Sep 2026

Side by side

Same prompt, both answers

Opening lines from 3 of the 16 prompts both answered. Formatting stripped, words untouched.

Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

GPT-5.2 Pro837 words

A simple, actionable 1‑month plan (3 pillars: Nutrition, Movement, Sleep/Recovery) Goal for the month: build repeatable “default” habits (not perfection). Time required: ~45–75 min/day total (mostly walking + sleep routine).

Read the full answer

Qwen3.8 Max Prime473 words

Your 1-Month Foundation Plan A simple, progressive plan built on three pillars. Each week, you add one small layer. No perfection required—just consistency. 🏃 Pillar 1: Movement Why: Even modest activity reduces all-cause mortality risk and improves mood, sleep, and energy within days.

Read the full answer

Advanced Investment Memo (IC Memo)

You are writing an internal investment committee memo for a long/short equity fund. Company (fictional): LedgerLift (ticker: LLLT) – B2B…

GPT-5.2 Pro484 words

LedgerLift (LLLT) — Internal IC Memo (Long/Short Equity) Recommendation, PT, thesis Recommendation: SHORT 12-month PT range: $28–$40 (midpoint $34) Thesis (2 sentences): LLLT is a high-quality B2B spend/AP automation SaaS business (92% subscription, 123% NRR, 78% FY25 GM) but the stock prices in a longer runway of…

Read the full answer

Qwen3.8 Max Prime1,001 words

INVESTMENT COMMITTEE MEMO LedgerLift (LLLT) B2B Spend Management & AP Automation SaaS Date: [Current] Analyst: [Name] Sector: Enterprise Software RECOMMENDATION LONG 12-Month Price Target: $50–$58 Current: $46 Thesis: LedgerLift is a high-quality compounder (123% NRR, 18-month CAC payback, 92% subscription mix) trading…

Read the full answer

Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

GPT-5.2 Pro161 words

Entry (close end of FY2025) FY2025 EBITDA = $120.0m Entry EV = 12.0x = 12.0 × 120.0 = $1,440.0m Transaction fees = 2.0% EV = 0.02 × 1,440.0 = $28.8m (equity-funded) Debt at close (5.5x EBITDA = 5.5 × 120 = $660m): Term Loan = 4.0x = $480.0m Mezzanine = 1.5x = $180.0m Equity check Uses = 1,440.0 + 28.8 = $1,468.8m…

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Qwen3.8 Max Prime673 words

HarborTech Services (HTS) – LBO Underwriting Memo Entry & Capital Structure Item Amount FY2025 EBITDA $120.0m Entry Multiple 12.0x Enterprise Value $1,440.0m Transaction Fees (2.0% of EV) $28.8m Total Uses $1,468.8m Term Loan (4.0x, 9.0% cash, 1.0% amort) $480.0m Mezzanine (1.5x, 12.0% cash + 2.0% PIK) $180.0m Sponsor…

Read the full answer

Our Verdict

GPT-5.2 Pro

Qwen3.8 Max Prime

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

Qwen3.8 Max Prime costs 14x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-5.2 Pro

Input

$21.00

Output

$168.00

Qwen3.8 Max Prime

Input

$4.00

5.3× cheaper

Output

$12.00

14× cheaper

Qwen3.8 Max Prime is cheaper on both: 5.3× input, 14× output.

Where to run it

2 hosts

GPT-5.2 Pro1 host

HostInOutContextUptime

OpenAI$21.00 in$168.00 out400k100% up

Qwen3.8 Max Prime1 host

HostInOutContextUptime

Alibaba Cloud$4.00 in$12.00 out1M99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Keep exploring

More comparisons

Same prompt, both answers

Beginner's Longevity Plan

Advanced Investment Memo (IC Memo)

Mini LBO Underwrite

Cost per 1M tokens

2 hosts

What we learned reading every model

Common questions

What is the difference between GPT-5.2 Pro and Qwen3.8 Max Prime?

Which is better, GPT-5.2 Pro or Qwen3.8 Max Prime?

How much does GPT-5.2 Pro cost compared to Qwen3.8 Max Prime?

How can I compare GPT-5.2 Pro and Qwen3.8 Max Prime on Rival?

More comparisons

Against the newest arrivals

Same lab, same size, long tail

Model pages

Same prompt, both answers

Beginner's Longevity Plan

Advanced Investment Memo (IC Memo)

Mini LBO Underwrite

Cost per 1M tokens

2 hosts

What we learned reading every model

Common questions

What is the difference between GPT-5.2 Pro and Qwen3.8 Max Prime?

Which is better, GPT-5.2 Pro or Qwen3.8 Max Prime?

How much does GPT-5.2 Pro cost compared to Qwen3.8 Max Prime?

How can I compare GPT-5.2 Pro and Qwen3.8 Max Prime on Rival?

More comparisons

Against the newest arrivals

Same lab, same size, long tail

Model pages