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  5. Qwen3 235B A22B Thinking 2507vsQwen3.8 Omni Flash
Updated Sep 2026

Qwen3 235B A22B Thinking 2507vsQwen3.8 Omni Flash

Qwen3 235B A22B Thinking 2507 is cheaper than Qwen3.8 Omni Flash at $0.11/M vs $0.15/M input tokens.

Qwen3 235B A22B Thinking 2507 and Qwen3.8 Omni Flash compared across 9 shared prompts
SpecQwen3 235B A22B Thinking 2507Qwen3.8 Omni Flash
Input price$0.11/M tokens$0.15/M tokens
Output price$0.6/M tokens$0.47/M tokens
Context window131K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2025Sep 2026
Side by side

Same prompt, both answers

Opening lines from 4 of the 9 prompts both answered. Formatting stripped, words untouched.

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.…

Qwen3 235B A22B Thinking 25071,700 words
Okay, the user wants me to analyze a pitch deck for a startup called MindMeld AI. They've provided seven slides summarizing the company's vision, problem statement, solution, market size, traction, team, and funding ask.
Read the full answer
Qwen3.8 Omni Flash2,971 words
The three weakest claims—ranked by how likely they are to fail investor diligence—are: “94% accuracy… works with any language, any device.” “TAM: $180B” based on 3.5B smartphone users. “FDA clearance” consuming 40% of the Series A raise.
Read the full answer

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…

Qwen3 235B A22B Thinking 2507327 words
🌟 "Pantry Firecracker Cinnamon Crisps" Sweet, crunchy, with a hint of smoky warmth—ready in 15 minutes! Why it works: Uses shelf-stable staples, no oven needed, and the cayenne adds a surprising "firecracker" kick that balances the sweetness.
Read the full answer
Qwen3.8 Omni Flash175 words
Buttery Cloud Pancakes A soft, golden pancake stack made with just 7 pantry staples—no special mix-ins, no fancy tools, just simple comfort. Ingredients All-purpose flour Granulated sugar Baking powder Fine salt Milk Egg Butter Prep Time 10 minutes Cook Time 12 minutes Serves 2–3 Instructions In a bowl, whisk together…
Read the full answer

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…

Qwen3 235B A22B Thinking 2507682 words
Here’s a simple, no-guilt, beginner-friendly 1-month plan focused on diet, movement, and sleep (the 3 most impactful, science-backed pillars for longevity). Designed for real people with busy lives—no apps, expensive tools, or drastic changes. Goal: Build consistent habits, not perfection. Why These 3 Areas?
Read the full answer
Qwen3.8 Omni Flash712 words
A Simple 1-Month Health & Longevity Starter Plan Goal: Build sustainable habits—not perfection—around diet, exercise, and recovery/sleep. Time commitment: Small daily actions plus 2–3 short workouts per week. The 3 Key Areas Diet: Add more good foods before restricting Beginner rule: Focus on adding, not removing.
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…

Qwen3 235B A22B Thinking 2507982 words
For the Experienced Software Engineer (Skeptical of "Next Word Prediction") You've built systems where behavior emerges from state transitions and message passing, so your skepticism about "next token prediction" creating intelligence is understandable—it sounds trivial.
Read the full answer
Qwen3.8 Omni Flash913 words
For the experienced software engineer A large language model is best thought of as a gigantic, parameterized probabilistic function that maps a sequence of tokens to a probability distribution over the next token.
Read the full answer
Our Verdict
Qwen3 235B A22B Thinking 2507
Qwen3 235B A22B Thinking 2507
Qwen3.8 Omni Flash
Qwen3.8 Omni Flash

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

Too close to call
API pricing

Cost per 1M tokens

Qwen3 235B A22B Thinking 2507
Input
$0.11
1.4× cheaper
Output
$0.60
Qwen3.8 Omni Flash
Input
$0.15
Output
$0.47
1.3× cheaper

Qwen3 235B A22B Thinking 2507 wins input (1.4× cheaper)·Qwen3.8 Omni Flash wins output (1.3× cheaper)

Where to run it

4 hosts, cheapest first

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·91.9% upVVenicefp8$0.45 in·$3.50 out·128k·90.3% up
Qwen3.8 Omni Flash1 host
HostInOutContextUptime
Alibaba Clouddegraded$0.15 in·$0.47 out·1M·99% up

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

Research

What we learned reading every model

FAQ

Common questions

Both are developed by Qwen but target different use cases. Qwen3 235B A22B Thinking 2507 has a 131K token context window vs Qwen3.8 Omni Flash's 1.0M. You can compare their actual outputs across 9 challenges on Rival to see how they differ in practice.

It depends on your use case. Qwen3 235B A22B Thinking 2507 and Qwen3.8 Omni Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 9 challenges so you can judge which fits your needs best.

Qwen3 235B A22B Thinking 2507 costs $0.11/M input tokens and Qwen3.8 Omni Flash costs $0.15/M input tokens. Qwen3 235B A22B Thinking 2507 is $0.04/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 Qwen3 235B A22B Thinking 2507 and Qwen3.8 Omni 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

Qwen3 235B A22B Thinking 2507 logo
Qwen3 235B A22B Thinking 250759 outputs, specs and price
Qwen3.8 Omni Flash logo
Qwen3.8 Omni Flash9 outputs, specs and price
Rival
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