ERNIE 4.5 vs MiniMax M2
MiniMax M2 leads the LLM Stats Score 27.3 to -12.9. MiniMax M2 is 2.5x cheaper per token.
Baidu · MiniMax · Updated for 2026
Which is better?
MiniMax M2 leads the overall LLM Stats Score 27.3 to -12.9, ranking #129 overall.
In the 2 individual benchmarks reported for both models, MiniMax M2 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, MiniMax M2 is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M2 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 ERNIE 4.5
- you want predictable pricing at $0.40/M input and $4.00/M output
Choose MiniMax M2
- overall performance matters — it scores 27.3 and ranks #129 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 2.5x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for ERNIE 4.5 · 16 for MiniMax M2
ERNIE 4.5 outperforms in 0 benchmarks, while MiniMax M2 is better at 2 benchmarks (GPQA, MMLU-Pro).
MiniMax M2 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, ERNIE 4.5 ($0.40/1M tokens) is 1.3x more expensive than MiniMax M2 ($0.30/1M tokens).
For output processing, ERNIE 4.5 ($4.00/1M tokens) is 3.3x more expensive than MiniMax M2 ($1.20/1M tokens).
In conclusion, ERNIE 4.5 is more expensive than MiniMax M2.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M2 has 209.0B more parameters than ERNIE 4.5, making it 995.2% larger.
Context Window
Maximum input and output token capacity
MiniMax M2 accepts 1,000,000 input tokens compared to ERNIE 4.5's 128,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while ERNIE 4.5 is limited to 65,536 tokens.
License
Usage and distribution terms
ERNIE 4.5 is licensed under a proprietary license, while MiniMax M2 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
ERNIE 4.5 was released on 2025-06-25, while MiniMax M2 was released on 2025-10-27.
MiniMax M2 is 4 months newer than ERNIE 4.5.
Jun 25, 2025
1.2 years ago
Oct 27, 2025
10 months ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
ERNIE 4.5 is available from Novita. MiniMax M2 is available from MiniMax, Novita.
ERNIE 4.5
MiniMax M2
Outputs Comparison
Judge for yourself.
Run your own prompts against ERNIE 4.5 and MiniMax M2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about ERNIE 4.5 vs MiniMax M2.