Model Comparison

ERNIE 4.5 vs Kimi K2 Instruct

Kimi K2 Instruct significantly outperforms across most benchmarks. Kimi K2 Instruct is 2.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

ERNIE 4.5 outperforms in 0 benchmarks, while Kimi K2 Instruct is better at 6 benchmarks (GPQA, GSM8k, MMLU, MMLU-Pro, MMLU-Redux, SimpleQA).

Kimi K2 Instruct significantly outperforms across most benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Kimi K2 Instruct costs less

For input processing, ERNIE 4.5 ($0.40/1M tokens) is 1.3x cheaper than Kimi K2 Instruct ($0.50/1M tokens).

For output processing, ERNIE 4.5 ($4.00/1M tokens) is 8.0x more expensive than Kimi K2 Instruct ($0.50/1M tokens).

In conclusion, ERNIE 4.5 is more expensive than Kimi K2 Instruct.*

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

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
Baidu
ERNIE 4.5
Input tokens$0.40
Output tokens$4.00
Best providerNovita
Moonshot AI
Kimi K2 Instruct
Input tokens$0.50
Output tokens$0.50
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

979.0B diff

Kimi K2 Instruct has 979.0B more parameters than ERNIE 4.5, making it 4661.9% larger.

Baidu
ERNIE 4.5
21.0Bparameters
Moonshot AI
Kimi K2 Instruct
1000.0Bparameters
21.0B
ERNIE 4.5
1000.0B
Kimi K2 Instruct

Context Window

Maximum input and output token capacity

Kimi K2 Instruct accepts 200,000 input tokens compared to ERNIE 4.5's 128,000 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while ERNIE 4.5 is limited to 65,536 tokens.

Baidu
ERNIE 4.5
Input128,000 tokens
Output65,536 tokens
Moonshot AI
Kimi K2 Instruct
Input200,000 tokens
Output200,000 tokens
Thu Apr 16 2026 • llm-stats.com

License

Usage and distribution terms

ERNIE 4.5 is licensed under a proprietary license, while Kimi K2 Instruct uses MIT.

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

ERNIE 4.5

Proprietary

Closed source

Kimi K2 Instruct

MIT

Open weights

Release Timeline

When each model was launched

ERNIE 4.5 was released on 2025-06-25, while Kimi K2 Instruct was released on 2025-07-11.

Kimi K2 Instruct is 1 month newer than ERNIE 4.5.

ERNIE 4.5

Jun 25, 2025

9 months ago

Kimi K2 Instruct

Jul 11, 2025

9 months ago

2w 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. Kimi K2 Instruct is available from Fireworks, Novita.

ERNIE 4.5

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

Kimi K2 Instruct

fireworks logo
Fireworks
Input Price:Input: $0.50/1MOutput Price:Output: $0.50/1M
novita logo
Novita
Input Price:Input: $0.57/1MOutput Price:Output: $2.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Baidu
Less expensive input tokens
Moonshot AI
Larger context window (200,000 tokens)
Less expensive output tokens
Has open weights
Higher GPQA score (75.1% vs 74.0%)
Higher GSM8k score (97.3% vs 25.2%)
Higher MMLU score (89.5% vs 41.9%)
Higher MMLU-Pro score (81.1% vs 16.0%)
Higher MMLU-Redux score (92.7% vs 43.2%)
Higher SimpleQA score (31.0% vs 1.8%)

Detailed Comparison

AI Model Comparison Table
Feature
Baidu
ERNIE 4.5
Moonshot AI
Kimi K2 Instruct

FAQ

Common questions about ERNIE 4.5 vs Kimi K2 Instruct

Kimi K2 Instruct significantly outperforms across most benchmarks. ERNIE 4.5 is made by Baidu and Kimi K2 Instruct is made by Moonshot AI. 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%. Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%.
ERNIE 4.5 is 1.3x cheaper for input tokens. ERNIE 4.5 costs $0.40/M input and $4.00/M output via novita. Kimi K2 Instruct costs $0.50/M input and $0.50/M output via fireworks.
ERNIE 4.5 supports 128K tokens and Kimi K2 Instruct supports 200K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (128K vs 200K), input pricing ($0.40 vs $0.50/M), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
ERNIE 4.5 is developed by Baidu and Kimi K2 Instruct is developed by Moonshot AI.