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  5. MiniMax M1vsQwen3.8 Max (0902)
Updated Sep 2026

MiniMax M1vsQwen3.8 Max (0902)

MiniMax M1 is cheaper than Qwen3.8 Max (0902) at $0.3/M vs $2/M input tokens.

MiniMax M1 and Qwen3.8 Max (0902) compared across 3 shared prompts
SpecMiniMax M1Qwen3.8 Max (0902)
Input price$0.3/M tokens$2/M tokens
Output price$1.65/M tokens$6/M tokens
Context window1.0M tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJun 2025Sep 2026
Side by side

Same prompt, both answers

Opening lines from 2 of the 3 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…

MiniMax M1672 words
Here's a delicious, fast, and flexible recipe using 7 common pantry staples: Dish Name: Sun-Drenched Chickpea Scramble (Inspired by chickpea "scrambles" or shakshuka variations, using pantry essentials) Flavor Profile: Savory, earthy, bright, slightly tangy, and warmly spiced.
Read the full answer
Qwen3.8 Max (0902)230 words
🍯 Midnight Crispy Chickpea Bowl A sweet-savory, crispy rice bowl that comes together faster than delivery. Ingredients (7) # Ingredient Amount 1 Canned chickpeas (drained & patted dry) 1 can (15 oz) 2 Soy sauce 3 tbsp 3 Honey 2 tbsp 4 Garlic (minced) 3 cloves 5 Vegetable oil 2 tbsp 6 Instant or leftover cooked rice 2…
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…

MiniMax M1763 words
For an Experienced Software Engineer Imagine you’re designing a distributed system where every API request is a snippet of text, and your system’s job is to predict the next word in the sequence. That’s essentially what a large language model (LLM) does.
Read the full answer
Qwen3.8 Max (0902)1,046 words
For the Experienced Software Engineer Think of an LLM as a lossy compression function trained on a massive corpus. During training, you're essentially building a statistical model of "given this sequence of tokens, what's the probability distribution over the next token?"
Read the full answer
Our Verdict
MiniMax M1
MiniMax M1
Qwen3.8 Max (0902)
Qwen3.8 Max (0902)

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

MiniMax M1 costs 3.6x less per token.

Too close to call
API pricing

Cost per 1M tokens

MiniMax M1
Input
$0.30
6.7× cheaper
Output
$1.65
3.6× cheaper
Qwen3.8 Max (0902)
Input
$2.00
Output
$6.00

MiniMax M1 is cheaper on both: 6.7× input, 3.6× output.

Where to run it

3 hosts, cheapest first

MiniMax M12 hosts
HostInOutContextUptime
MiniMax$0.40 in·$2.20 out·1M·100% upNNovitabf16$0.55 in·$2.20 out·1M·100% up
Qwen3.8 Max (0902)1 host
HostInOutContextUptime
Alibaba Cloud$2.00 in·$6.00 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

MiniMax M1 is developed by MiniMax while Qwen3.8 Max (0902) is developed by Qwen. MiniMax M1 has a 1.0M token context window vs Qwen3.8 Max (0902)'s 1.0M. You can compare their actual outputs across 3 challenges on Rival to see how they differ in practice.

It depends on your use case. MiniMax M1 and Qwen3.8 Max (0902) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 3 challenges so you can judge which fits your needs best.

MiniMax M1 costs $0.3/M input tokens and Qwen3.8 Max (0902) costs $2/M input tokens. MiniMax M1 is $1.70/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 MiniMax M1 and Qwen3.8 Max (0902) 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

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Qwen3.8 Max (0902) logo
Qwen3.8 Max (0902)3 outputs, specs and price
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