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  5. GPT-5.4 NanovsQwen3.7 Flash
Updated Jul 2026

GPT-5.4 NanovsQwen3.7 Flash

Qwen3.7 Flash is cheaper than GPT-5.4 Nano at $0.03/M vs $0.2/M input tokens.

GPT-5.4 Nano and Qwen3.7 Flash compared across 13 shared prompts
SpecGPT-5.4 NanoQwen3.7 Flash
Input price$0.2/M tokens$0.03/M tokens
Output price$1.25/M tokens$0.13/M tokens
Context window400K tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedMar 2026Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 prompts both answered. Formatting stripped, words untouched.

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

GPT-5.4 Nano184 words
Dish Name: Golden Garlic Chickpea Clouds Pantry Ingredients (7 total) Chickpeas (canned or cooked) – 1 can (15 oz), drained Olive oil – 2 tbsp Garlic – 3 cloves (or 1–2 tsp minced garlic) Lemon – 1 (you’ll use the juice) Salt – 1/2 tsp (plus to taste) Black pepper – 1/4 tsp (plus to taste) Paprika – 1 tsp Estimated…
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Qwen3.7 Flash332 words
🥔 Golden Crunch Smash-Roasted Potatoes A crowd-pleasing side dish that delivers maximum crispiness with minimal effort. By boiling then smashing the potatoes before roasting, you create a shatteringly crisp crust while keeping the inside fluffy. This recipe relies on just seven pantry staples for perfect flavor.
Read the full answer

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-5.4 Nano1,825 words
Below is a practical, risk-aware 48-hour plan designed to (1) protect patients immediately, (2) meet likely regulatory expectations even if formal reporting takes months, (3) reduce legal exposure by demonstrating diligence and good faith, and (4) stabilize the market with an ethical, transparent communications…
Read the full answer
Qwen3.7 Flash1,240 words
This is a high-stakes crisis requiring decisive, legally compliant, ethically grounded, and strategically coordinated action. Below is a structured, hour-by-hour executive playbook for the next 48 hours, followed by cross-cutting rationale addressing your specified dimensions.
Read the full answer

Adversarial Contract Review

Here is a contract for a software consulting engagement: --- SOFTWARE CONSULTING AGREEMENT This Agreement is entered into between TechCorp…

GPT-5.4 Nano1,859 words
I’m not a lawyer, but I can flag contract terms that (a) are unusually one‑sided, (b) create open‑ended or high‑risk obligations, or (c) can be interpreted in ways that materially disadvantage the contractor. I’ll then suggest specific counter‑edits and explain the typical legal/contracting rationale.
Read the full answer
Qwen3.7 Flash1,322 words
This agreement contains several highly one-sided provisions that create significant legal, financial, and operational risks for the contractor. Below is a clause-by-clause analysis identifying exploitation risks, recommended modifications, and the underlying legal reasoning. Note: Contract law varies by jurisdiction.
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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-5.4 Nano785 words
Here’s a simple, actionable 1‑month plan focused on 3 key areas: food, movement, and sleep/stress. It’s designed for beginners and is intentionally realistic. Overall goal (simple) Each week, build consistency in: Food: more whole foods + fewer “defaults” Exercise: daily movement + 2–3 strength sessions/week Sleep +…
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Qwen3.7 Flash763 words
🌱 30-Day Health & Longevity Starter Plan This plan focuses on the three most evidence-backed pillars of longevity: Nutrition, Movement, and Sleep/Recovery. It’s designed for beginners: low barrier to entry, zero equipment required, and built on consistency over intensity. You’ll progress gradually so habits stick.
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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-5.4 Nano1,050 words
Experienced software engineer (distributed systems / APIs, skeptical about “next-word”) A large language model (LLM) is trained on huge corpora by learning statistical patterns that map a sequence of tokens (text subunits) to likely continuations—so yes, at the core it’s “predict the next token.”
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Qwen3.7 Flash1,038 words
For the Experienced Software Engineer Think of an LLM’s training process less as “teaching” and more as optimizing a high-dimensional function across a petabyte-scale dataset, much like you’d architect a distributed system to handle massive throughput.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

GPT-5.4 Nano2,226 words
Below is a counterfactual “timeline-style” trace assuming the first practical transistor (or something functionally equivalent) existed in 1920 and that from then on semiconductor device physics, fabrication know-how, and manufacturing learning proceeded along the easiest path consistent with 1920-era science and…
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Qwen3.7 Flash1,381 words
This counterfactual traces a plausible diffusion curve for an early transistor invention, acknowledging that while the underlying physics could be known in 1920, practical adoption would be constrained by materials science, precision manufacturing, and institutional readiness.
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Our Verdict
Qwen3.7 Flash
Qwen3.7 Flash
GPT-5.4 Nano
GPT-5.4 NanoRunner-up

Not enough votes to call it. On the specs, Qwen3.7 Flash has the edge: bigger model tier, newer, bigger context window.

Qwen3.7 Flash costs 9.6x less per token.

Too close to call
API pricing

Cost per 1M tokens

GPT-5.4 Nano
Input
$0.20
Output
$1.25
Qwen3.7 Flash
Input
$0.03
6.7× cheaper
Output
$0.13
9.6× cheaper

Qwen3.7 Flash is cheaper on both: 6.7× input, 9.6× output.

Where to run it

3 hosts

GPT-5.4 Nano2 hosts
HostInOutContextUptime
Azure AI Foundry$0.20 in·$1.25 out·400k·100% upOpenAI$0.20 in·$1.25 out·400k·100% up
Qwen3.7 Flash1 host
HostInOutContextUptime
Alibaba Cloud$0.03 in·$0.13 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 22 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GPT-5.4 Nano is developed by OpenAI while Qwen3.7 Flash is developed by Qwen. GPT-5.4 Nano has a 400K token context window vs Qwen3.7 Flash's 1.0M. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5.4 Nano and Qwen3.7 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 13 challenges so you can judge which fits your needs best.

GPT-5.4 Nano costs $0.2/M input tokens and Qwen3.7 Flash costs $0.03/M input tokens. Qwen3.7 Flash is $0.17/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 Nano and Qwen3.7 Flash 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-5.4 Nano logo
GPT-5.4 Nano53 outputs, specs and price
Qwen3.7 Flash logo
Qwen3.7 Flash13 outputs, specs and price
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