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  5. Kimi K2.6vsQwen3.8 Flash
Updated Aug 2026

Kimi K2.6vsQwen3.8 Flash

Qwen3.8 Flash is cheaper than Kimi K2.6 at $0.15/M vs $0.95/M input tokens.

Kimi K2.6 and Qwen3.8 Flash compared across 8 shared prompts
SpecKimi K2.6Qwen3.8 Flash
Input price$0.95/M tokens$0.15/M tokens
Output price$4/M tokens$0.47/M tokens
Context window262K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedApr 2026Aug 2026
Side by side

Same prompt, both answers

Opening lines from 3 of the 8 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…

Kimi K2.6286 words
The Blanket Fort Stew (Rustic One-Pot Pasta e Ceci) A warm, garlicky hug of a meal built from true shelf-stable staples. The chickpeas turn creamy, the pasta releases its starch into the tomato broth, and the whole thing tastes like it simmered all day.
Read the full answer
Qwen3.8 Flash147 words
Moon Halo Cookies A soft, golden sugar cookie with crisp edges and a tender center—made with just 7 pantry staples. Prep time: 10 minutes Cook time: 10 minutes Total time: 20 minutes Makes: About 16 cookies Ingredients 1/2 cup butter, softened 3/4 cup sugar 1 egg 1 teaspoon vanilla extract 1 1/2 cups all-purpose flour…
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…

Kimi K2.6549 words
The Foundation Month: A 30-Day Longevity Starter Plan Philosophy: Don’t overhaul your life. Stack one small win at a time so habits stick. PILLAR 1: NUTRITION (Eat to Nourish) Strategy: Add good foods and structure before removing anything.
Read the full answer
Qwen3.8 Flash368 words
1-Month Beginner Health & Longevity Plan Focus areas: Nutrition, Movement, Sleep Week 1: Build the basics Nutrition Add 1 serving of vegetables to 2 meals per day. Drink water with each meal. Choose protein at most meals: eggs, beans, tofu, chicken, fish, yogurt. Movement Walk 10–15 minutes daily.
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…

Kimi K2.6877 words
1. Experienced Software Engineer Think of an LLM not as a program you write, but as a binary you compile from the entire internet. Instead of hand-crafting if/then rules, you define a single objective: given the context "The cat sat on the...", output the probability distribution over every possible next token, and…
Read the full answer
Qwen3.8 Flash983 words
For an experienced software engineer Training a large language model is not “just” making it guess the next word in isolation. It is fitting an enormous parameterized function to predict the next token conditioned on all previous tokens in a sequence.
Read the full answer
Our Verdict
Qwen3.8 Flash
Qwen3.8 Flash
Kimi K2.6
Kimi K2.6Runner-up

Not enough votes to call it. On the specs, Qwen3.8 Flash has the edge: newer, bigger context window.

Qwen3.8 Flash costs 8.5x less per token.

Too close to call
API pricing

Cost per 1M tokens

Kimi K2.6
Input
$0.95
Output
$4.00
Qwen3.8 Flash
Input
$0.15
6.3× cheaper
Output
$0.47
8.5× cheaper

Qwen3.8 Flash is cheaper on both: 6.3× input, 8.5× output.

Where to run it

22 hosts, cheapest first

Kimi K2.621 hosts
HostInOutContextUptime
IInceptronint4$0.50 in·$2.97 out·262k·99.7% upCChutesint4$0.50 in·$2.85 out·262k·98.8% upDDigitalOcean$0.57 in·$2.40 out·262k·98.3% upSStreamLakefp8$0.60 in·$2.52 out·256k·99% upCCoreWeavefp4$0.65 in·$3.41 out·262k·99.9% upDDeepInfrafp4$0.75 in·$3.50 out·262k·97.1% up
15 more hostsFewer hosts
PParasailint4$0.75 in·$3.50 out·262k·99.6% upVVeniceint4$0.75 in·$3.50 out·256k·95.9% upSSiliconFlowfp8$0.77 in·$3.40 out·262k·99.7% upNNovita$0.80 in·$3.40 out·262k·99.8% upGGMI Cloudfp8$0.85 in·$3.60 out·262k·86.7% upBaidu Qianfanfp4$0.95 in·$4.00 out·262k·100% upBBasetenfp4$0.95 in·$4.00 out·262k·97.2% upCloudflare Workers AI$0.95 in·$4.00 out·262k·99.2% upFFireworks$0.95 in·$4.00 out·262k·0% upMoonshot AIint4$0.95 in·$4.00 out·262k·99.9% upSSail Researchint4$1.00 in·$4.00 out·262k·100% upPPhala$1.09 in·$4.60 out·262k·99.7% upDDecartfp4degraded$0.59 in·$2.47 out·262k·98.4% upCCrusoebf16degraded$0.70 in·$3.50 out·262k·98.2% upAAtlasCloudint4degraded$0.95 in·$4.00 out·262k·98% up
Qwen3.8 Flash1 host
HostInOutContextUptime
Alibaba Cloud$0.15 in·$0.47 out·1M·100% up

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

Research

What we learned reading every model

FAQ

Common questions

Kimi K2.6 is developed by Moonshot AI while Qwen3.8 Flash is developed by Qwen. Kimi K2.6 has a 262K token context window vs Qwen3.8 Flash's 1.0M. You can compare their actual outputs across 8 challenges on Rival to see how they differ in practice.

It depends on your use case. Kimi K2.6 and Qwen3.8 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 8 challenges so you can judge which fits your needs best.

Kimi K2.6 costs $0.95/M input tokens and Qwen3.8 Flash costs $0.15/M input tokens. Qwen3.8 Flash is $0.80/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 Kimi K2.6 and Qwen3.8 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

Kimi K2.6 logo
Kimi K2.658 outputs, specs and price
Qwen3.8 Flash logo
Qwen3.8 Flash8 outputs, specs and price
Rival
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