Model Comparison

ERNIE 5.0 vs LongCat-Flash-Thinking

ERNIE 5.0 shows notably better performance in the majority of benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

ERNIE 5.0 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while LongCat-Flash-Thinking is better at 1 benchmark (AIME 2025).

ERNIE 5.0 shows notably better performance in the majority of benchmarks.

Wed Apr 15 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
Wed Apr 15 2026 • llm-stats.com
Baidu
ERNIE 5.0
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Meituan
LongCat-Flash-Thinking
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Thinking specifies input context (128,000 tokens). Only LongCat-Flash-Thinking specifies output context (128,000 tokens).

Baidu
ERNIE 5.0
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

ERNIE 5.0 supports multimodal inputs, whereas LongCat-Flash-Thinking does not.

ERNIE 5.0 can handle both text and other forms of data like images, making it suitable for multimodal applications.

ERNIE 5.0

Text
Images
Audio
Video

LongCat-Flash-Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

ERNIE 5.0 is licensed under a proprietary license, while LongCat-Flash-Thinking uses MIT.

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

ERNIE 5.0

Proprietary

Closed source

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

ERNIE 5.0 was released on 2025-01-22, while LongCat-Flash-Thinking was released on 2025-09-22.

LongCat-Flash-Thinking is 8 months newer than ERNIE 5.0.

ERNIE 5.0

Jan 22, 2025

1.2 years ago

LongCat-Flash-Thinking

Sep 22, 2025

6 months ago

8mo 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Baidu
Supports multimodal inputs
Higher GPQA score (85.0% vs 81.5%)
Higher MMLU-Pro score (87.0% vs 82.6%)
Meituan
Larger context window (128,000 tokens)
Has open weights
Higher AIME 2025 score (90.6% vs 87.0%)

Detailed Comparison

AI Model Comparison Table
Feature
Baidu
ERNIE 5.0
Meituan
LongCat-Flash-Thinking

FAQ

Common questions about ERNIE 5.0 vs LongCat-Flash-Thinking

ERNIE 5.0 shows notably better performance in the majority of benchmarks. ERNIE 5.0 is made by Baidu and LongCat-Flash-Thinking is made by Meituan. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
ERNIE 5.0 scores AIME 2025: 87.0%, MMLU-Pro: 87.0%, GPQA: 85.0%, SimpleQA: 75.0%, Humanity's Last Exam: 39.0%. LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%.
ERNIE 5.0 supports an unknown number of tokens and LongCat-Flash-Thinking supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
ERNIE 5.0 is developed by Baidu and LongCat-Flash-Thinking is developed by Meituan.