Claude 3.5 Sonnet vs Kimi-k1.5 Comparison

Comparing Claude 3.5 Sonnet and Kimi-k1.5 across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Claude 3.5 Sonnet outperforms in 1 benchmarks (MMLU), while Kimi-k1.5 is better at 2 benchmarks (MathVista, MMMU).

Kimi-k1.5 shows notably better performance in the majority of benchmarks.

Fri Mar 20 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
Fri Mar 20 2026 • llm-stats.com
Anthropic
Claude 3.5 Sonnet
Input tokens$3.00
Output tokens$15.00
Best providerAnthropic
Moonshot AI
Kimi-k1.5
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Context Window

Maximum input and output token capacity

Only Claude 3.5 Sonnet specifies input context (200,000 tokens). Only Claude 3.5 Sonnet specifies output context (200,000 tokens).

Anthropic
Claude 3.5 Sonnet
Input200,000 tokens
Output200,000 tokens
Moonshot AI
Kimi-k1.5
Input- tokens
Output- tokens
Fri Mar 20 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Claude 3.5 Sonnet and Kimi-k1.5 support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Claude 3.5 Sonnet

Text
Images
Audio
Video

Kimi-k1.5

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Claude 3.5 Sonnet

Proprietary

Closed source

Kimi-k1.5

Proprietary

Closed source

Release Timeline

When each model was launched

Claude 3.5 Sonnet was released on 2024-10-22, while Kimi-k1.5 was released on 2025-01-20.

Kimi-k1.5 is 3 months newer than Claude 3.5 Sonnet.

Claude 3.5 Sonnet

Oct 22, 2024

1.4 years ago

Kimi-k1.5

Jan 20, 2025

1.2 years ago

3mo 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

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Key Takeaways

Larger context window (200,000 tokens)
Higher MMLU score (90.4% vs 87.4%)
Higher MathVista score (74.9% vs 67.7%)
Higher MMMU score (70.0% vs 68.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Anthropic
Claude 3.5 Sonnet
Moonshot AI
Kimi-k1.5