Model Comparison

ERNIE 4.5 vs Gemma 2 27B

Gemma 2 27B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

ERNIE 4.5 outperforms in 0 benchmarks, while Gemma 2 27B is better at 9 benchmarks (AGIEval, ARC-C, ARC-E, GSM8k, HellaSwag, MATH, MMLU, PIQA, Winogrande).

Gemma 2 27B significantly outperforms across most benchmarks.

Tue Apr 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Baidu
ERNIE 4.5
Input tokens$0.40
Output tokens$4.00
Best providerNovita
Google
Gemma 2 27B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

6.2B diff

Gemma 2 27B has 6.2B more parameters than ERNIE 4.5, making it 29.5% larger.

Baidu
ERNIE 4.5
21.0Bparameters
Google
Gemma 2 27B
27.2Bparameters
21.0B
ERNIE 4.5
27.2B
Gemma 2 27B

Context Window

Maximum input and output token capacity

Only ERNIE 4.5 specifies input context (128,000 tokens). Only ERNIE 4.5 specifies output context (65,536 tokens).

Baidu
ERNIE 4.5
Input128,000 tokens
Output65,536 tokens
Google
Gemma 2 27B
Input- tokens
Output- tokens
Tue Apr 14 2026 • llm-stats.com

License

Usage and distribution terms

ERNIE 4.5 is licensed under a proprietary license, while Gemma 2 27B uses Gemma.

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

ERNIE 4.5

Proprietary

Closed source

Gemma 2 27B

Gemma

Open weights

Release Timeline

When each model was launched

ERNIE 4.5 was released on 2025-06-25, while Gemma 2 27B was released on 2024-06-27.

ERNIE 4.5 is 12 months newer than Gemma 2 27B.

ERNIE 4.5

Jun 25, 2025

9 months ago

12mo newer
Gemma 2 27B

Jun 27, 2024

1.8 years ago

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Baidu
Larger context window (128,000 tokens)
Google
Has open weights
Higher AGIEval score (55.1% vs 28.5%)
Higher ARC-C score (71.4% vs 40.6%)
Higher ARC-E score (88.6% vs 60.7%)
Higher GSM8k score (74.0% vs 25.2%)
Higher HellaSwag score (86.4% vs 33.0%)
Higher MATH score (42.3% vs 12.4%)
Higher MMLU score (75.2% vs 41.9%)
Higher PIQA score (83.2% vs 55.2%)
Higher Winogrande score (83.7% vs 51.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Baidu
ERNIE 4.5
Google
Gemma 2 27B

FAQ

Common questions about ERNIE 4.5 vs Gemma 2 27B

Gemma 2 27B significantly outperforms across most benchmarks. ERNIE 4.5 is made by Baidu and Gemma 2 27B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
ERNIE 4.5 scores GPQA: 74.0%, ARC-E: 60.7%, PIQA: 55.2%, Winogrande: 51.3%, CLUEWSC: 48.6%. Gemma 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%.
ERNIE 4.5 supports 128K tokens and Gemma 2 27B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Proprietary vs Gemma). See the full comparison above for benchmark-by-benchmark results.
ERNIE 4.5 is developed by Baidu and Gemma 2 27B is developed by Google.