MiniMax M3 vs Qwen3.8-27B
MiniMax M3 and Qwen3.8-27B are closely matched at 41.4 and 45.1 on the LLM Stats Score. MiniMax M3 is 2.2x cheaper per token.
MiniMax · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiniMax M3 and Qwen3.8-27B are closely matched on the overall LLM Stats Score at 41.4 and 45.1.
In the 5 individual benchmarks reported for both models, Qwen3.8-27B wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, MiniMax M3 is roughly 2.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M3 also accepts a larger context window (524,288 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose MiniMax M3
- cost matters — it's about 2.2x cheaper per token
- you process long inputs — it offers a 524,288 token context window
Choose Qwen3.8-27B
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
35 reported for MiniMax M3 · 26 for Qwen3.8-27B
MiniMax M3 outperforms in 1 benchmarks (OmniDocBench 1.5), while Qwen3.8-27B is better at 4 benchmarks (NL2Repo, OSWorld-Verified, SWE-Bench Pro, Terminal-Bench 2.1).
Qwen3.8-27B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M3 ($0.28/1M tokens) is 1.4x cheaper than Qwen3.8-27B ($0.40/1M tokens).
For output processing, MiniMax M3 ($1.10/1M tokens) is 2.7x cheaper than Qwen3.8-27B ($3.00/1M tokens).
In conclusion, Qwen3.8-27B is more expensive than MiniMax M3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M3 has 400.2B more parameters than Qwen3.8-27B, making it 1440.6% larger.
Context Window
Maximum input and output token capacity
MiniMax M3 accepts 524,288 input tokens compared to Qwen3.8-27B's 262,144 tokens. MiniMax M3 can generate longer responses up to 524,288 tokens, while Qwen3.8-27B is limited to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
Both MiniMax M3 and Qwen3.8-27B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
MiniMax M3
Qwen3.8-27B
License
Usage and distribution terms
MiniMax M3 is licensed under MIT, while Qwen3.8-27B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
MiniMax M3 was released on 2026-06-01, while Qwen3.8-27B was released on 2026-08-14.
Qwen3.8-27B is 2 months newer than MiniMax M3.
Jun 1, 2026
3 months ago
Aug 14, 2026
1 months ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M3 is available from DeepInfra, Fireworks, MiniMax, Novita, Together. Qwen3.8-27B is available from DeepInfra, FriendliAI.
MiniMax M3
Qwen3.8-27B
Outputs Comparison
Judge for yourself.
Run your own prompts against MiniMax M3 and Qwen3.8-27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M3 vs Qwen3.8-27B.