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Claude Haiku 5.5 vs Kimi K2-Instruct-0905

Claude Haiku 5.5 leads the LLM Stats Score 50.0 to 21.5.

Anthropic · Moonshot AI · Updated for 2026

Which is better?

Claude Haiku 5.5 leads the overall LLM Stats Score 50.0 to 21.5, ranking #19 overall.

In the 1 individual benchmarks reported for both models, Claude Haiku 5.5 wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Claude Haiku 5.5

  • overall performance matters — it scores 50.0 and ranks #19 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Kimi K2-Instruct-0905

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Claude Haiku 5.5
Anthropic
Kimi K2-Instruct-0905
Moonshot AI
Core performance indexes
LLM Stats Score
50.0
#19
21.5
#202
Reasoning
47.2
#27
21.8
#192
Coding
40.2
#13
9.6
#184
Agents
33.3
#28
-4.2
#197
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.10 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,000,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Claude Haiku 5.5
Kimi K2-Instruct-0905
Math
25.7#110
21.5#150
Tool use
20.3#59
6.4#156
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

36 reported for Claude Haiku 5.5 · 29 for Kimi K2-Instruct-0905

1 shared

Claude Haiku 5.5 outperforms in 1 benchmarks (SWE-bench Multilingual), while Kimi K2-Instruct-0905 is better at 0 benchmarks.

Claude Haiku 5.5 significantly outperforms across most benchmarks.

Fri Oct 09 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Claude Haiku 5.5 specifies input context (1,000,000 tokens). Only Claude Haiku 5.5 specifies output context (128,000 tokens).

Anthropic
Claude Haiku 5.5
Input1,000,000 tokens
Output128,000 tokens
Moonshot AI
Kimi K2-Instruct-0905
Input- tokens
Output- tokens
Fri Oct 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Claude Haiku 5.5 supports multimodal inputs, whereas Kimi K2-Instruct-0905 does not.

Claude Haiku 5.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Claude Haiku 5.5

Text
Images
Audio
Video

Kimi K2-Instruct-0905

Text
Images
Audio
Video

License

Usage and distribution terms

Claude Haiku 5.5 is licensed under a proprietary license, while Kimi K2-Instruct-0905 uses MIT.

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

Claude Haiku 5.5

Proprietary

Closed source

Kimi K2-Instruct-0905

MIT

Open weights

Release Timeline

When each model was launched

Claude Haiku 5.5 was released on 2026-10-07, while Kimi K2-Instruct-0905 was released on 2025-09-05.

Claude Haiku 5.5 is 13 months newer than Kimi K2-Instruct-0905.

Claude Haiku 5.5

Oct 7, 2026

1 days ago

1.1yr newer
Kimi K2-Instruct-0905

Sep 5, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

Claude Haiku 5.5 has a documented knowledge cutoff of 2026-06-01, while Kimi K2-Instruct-0905's cutoff date is not specified.

We can confirm Claude Haiku 5.5's training data extends to 2026-06-01, but cannot make a direct comparison without Kimi K2-Instruct-0905's cutoff date.

Claude Haiku 5.5

Jun 2026

Kimi K2-Instruct-0905

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Claude Haiku 5.5 and Kimi K2-Instruct-0905 side-by-side, then vote on the output you prefer.

Claude Haiku 5.5
✓ Preferred
Kimi K2-Instruct-0905
Open in Playground

FAQ

Common questions about Claude Haiku 5.5 vs Kimi K2-Instruct-0905.

Which is better, Claude Haiku 5.5 or Kimi K2-Instruct-0905?

Claude Haiku 5.5 leads the LLM Stats Score 50.0 to 21.5. Claude Haiku 5.5 is made by Anthropic and Kimi K2-Instruct-0905 is made by Moonshot AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Claude Haiku 5.5 compare to Kimi K2-Instruct-0905 in benchmarks?

Claude Haiku 5.5 scores Global-MMLU: 87.8%, MILU: 87.6%, BenchCAD (with Python tool): 87.0%, Chartography: 86.2%, SWE-bench Multilingual: 83.7%. Kimi K2-Instruct-0905 scores MATH-500: 97.4%, MMLU-Redux: 92.7%, IFEval: 89.8%, AutoLogi: 89.5%, MMLU: 89.5%.

What are the context window sizes for Claude Haiku 5.5 and Kimi K2-Instruct-0905?

Claude Haiku 5.5 supports 1.0M tokens and Kimi K2-Instruct-0905 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Claude Haiku 5.5 and Kimi K2-Instruct-0905?

Key differences include LLM Stats Score (50.0 vs 21.5), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Claude Haiku 5.5 and Kimi K2-Instruct-0905?

Claude Haiku 5.5 is developed by Anthropic and Kimi K2-Instruct-0905 is developed by Moonshot AI.

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