Model Comparison

ERNIE 4.5 vs MiniMax M2.1Which is better in 2026?

MiniMax M2.1 significantly outperforms across most benchmarks. MiniMax M2.1 is 2.5x cheaper per token.

Verdict: ERNIE 4.5 vs MiniMax M2.1 — which is better?

ERNIE 4.5 (by Baidu) and MiniMax M2.1 (by MiniMax) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

ERNIE 4.5 outperforms in 0 benchmarks, while MiniMax M2.1 is better at 2 benchmarks (GPQA, MMLU-Pro). MiniMax M2.1 significantly outperforms across most benchmarks.

On price, MiniMax M2.1 is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

MiniMax M2.1 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose ERNIE 4.5 if…

  • you want predictable pricing at $0.40/M input and $4.00/M output

Choose MiniMax M2.1 if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • 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 Dec 2025
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

ERNIE 4.5 outperforms in 0 benchmarks, while MiniMax M2.1 is better at 2 benchmarks (GPQA, MMLU-Pro).

MiniMax M2.1 significantly outperforms across most benchmarks.

Tue Jun 09 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

MiniMax M2.1 costs less

For input processing, ERNIE 4.5 ($0.40/1M tokens) is 1.3x more expensive than MiniMax M2.1 ($0.30/1M tokens).

For output processing, ERNIE 4.5 ($4.00/1M tokens) is 3.3x more expensive than MiniMax M2.1 ($1.20/1M tokens).

In conclusion, ERNIE 4.5 is more expensive than MiniMax M2.1.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Jun 09 2026 • llm-stats.com
Baidu
ERNIE 4.5
Input tokens$0.40
Output tokens$4.00
Best providerNovita
MiniMax
MiniMax M2.1
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

209.0B diff

MiniMax M2.1 has 209.0B more parameters than ERNIE 4.5, making it 995.2% larger.

Baidu
ERNIE 4.5
21.0Bparameters
MiniMax
MiniMax M2.1
230.0Bparameters
21.0B
ERNIE 4.5
230.0B
MiniMax M2.1

Context Window

Maximum input and output token capacity

MiniMax M2.1 accepts 1,000,000 input tokens compared to ERNIE 4.5's 128,000 tokens. MiniMax M2.1 can generate longer responses up to 1,000,000 tokens, while ERNIE 4.5 is limited to 65,536 tokens.

Baidu
ERNIE 4.5
Input128,000 tokens
Output65,536 tokens
MiniMax
MiniMax M2.1
Input1,000,000 tokens
Output1,000,000 tokens
Tue Jun 09 2026 • llm-stats.com

License

Usage and distribution terms

ERNIE 4.5 is licensed under a proprietary license, while MiniMax M2.1 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

ERNIE 4.5

Proprietary

Closed source

MiniMax M2.1

MIT

Open weights

Release Timeline

When each model was launched

ERNIE 4.5 was released on 2025-06-25, while MiniMax M2.1 was released on 2025-12-23.

MiniMax M2.1 is 6 months newer than ERNIE 4.5.

ERNIE 4.5

Jun 25, 2025

11 months ago

MiniMax M2.1

Dec 23, 2025

5 months ago

6mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

ERNIE 4.5 is available from Novita. MiniMax M2.1 is available from MiniMax.

ERNIE 4.5

novita logo
Novita
Input Price:Input: $0.40/1MOutput Price:Output: $4.00/1M

MiniMax M2.1

minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Baidu

No standout differentiators in the data we have for this pair.

MiniMax
Larger context window (1,000,000 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (81.0% vs 74.0%)
Higher MMLU-Pro score (88.0% vs 16.0%)

Detailed Comparison

AI Model Comparison Table
Feature
Baidu
ERNIE 4.5
MiniMax
MiniMax M2.1

FAQ

Common questions about ERNIE 4.5 vs MiniMax M2.1.

Which is better, ERNIE 4.5 or MiniMax M2.1?

MiniMax M2.1 significantly outperforms across most benchmarks. ERNIE 4.5 is made by Baidu and MiniMax M2.1 is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does ERNIE 4.5 compare to MiniMax M2.1 in benchmarks?

ERNIE 4.5 scores GPQA: 74.0%, ARC-E: 60.7%, PIQA: 55.2%, Winogrande: 51.3%, CLUEWSC: 48.6%. MiniMax M2.1 scores VIBE Web: 91.5%, VIBE Android: 89.7%, VIBE: 88.6%, MMLU-Pro: 88.0%, VIBE iOS: 88.0%.

Is ERNIE 4.5 cheaper than MiniMax M2.1?

MiniMax M2.1 is 1.3x cheaper for input tokens. ERNIE 4.5 costs $0.40/M input and $4.00/M output via novita. MiniMax M2.1 costs $0.30/M input and $1.20/M output via minimax.

What are the context window sizes for ERNIE 4.5 and MiniMax M2.1?

ERNIE 4.5 supports 128K tokens and MiniMax M2.1 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between ERNIE 4.5 and MiniMax M2.1?

Key differences include context window (128K vs 1.0M), input pricing ($0.40 vs $0.30/M), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes ERNIE 4.5 and MiniMax M2.1?

ERNIE 4.5 is developed by Baidu and MiniMax M2.1 is developed by MiniMax.

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