MiniMax M1 80K vs Qwen3 30B A3B
MiniMax M1 80K and Qwen3 30B A3B are closely matched at 21.8 and 17.6 on the LLM Stats Score. Qwen3 30B A3B is 6.4x cheaper per token.
MiniMax · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiniMax M1 80K and Qwen3 30B A3B are closely matched on the overall LLM Stats Score at 21.8 and 17.6.
In the 4 individual benchmarks reported for both models, MiniMax M1 80K wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 30B A3B is roughly 6.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M1 80K also accepts a larger context window (1,000,000 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 M1 80K
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Jun 2025
Choose Qwen3 30B A3B
- cost matters — it's about 6.4x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for MiniMax M1 80K · 8 for Qwen3 30B A3B
MiniMax M1 80K outperforms in 4 benchmarks (AIME 2024, AIME 2025, GPQA, LiveCodeBench), while Qwen3 30B A3B is better at 0 benchmarks.
MiniMax M1 80K 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 M1 80K ($0.55/1M tokens) is 5.5x more expensive than Qwen3 30B A3B ($0.10/1M tokens).
For output processing, MiniMax M1 80K ($2.20/1M tokens) is 7.3x more expensive than Qwen3 30B A3B ($0.30/1M tokens).
In conclusion, MiniMax M1 80K is more expensive than Qwen3 30B A3B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M1 80K has 425.5B more parameters than Qwen3 30B A3B, making it 1395.1% larger.
Context Window
Maximum input and output token capacity
MiniMax M1 80K accepts 1,000,000 input tokens compared to Qwen3 30B A3B's 128,000 tokens. Qwen3 30B A3B can generate longer responses up to 128,000 tokens, while MiniMax M1 80K is limited to 40,000 tokens.
License
Usage and distribution terms
MiniMax M1 80K is licensed under MIT, while Qwen3 30B A3B 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 M1 80K was released on 2025-06-16, while Qwen3 30B A3B was released on 2025-04-29.
MiniMax M1 80K is 2 months newer than Qwen3 30B A3B.
Jun 16, 2025
1.2 years ago
1mo newerApr 29, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M1 80K is available from Novita. Qwen3 30B A3B is available from DeepInfra, Novita, Fireworks.
MiniMax M1 80K
Qwen3 30B A3B
Outputs Comparison
Judge for yourself.
Run your own prompts against MiniMax M1 80K and Qwen3 30B A3B side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M1 80K vs Qwen3 30B A3B.