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Kimi-k1.5 vs Llama 3.2 11B Instruct

Kimi-k1.5 leads the LLM Stats Score 17.2 to -1.3.

Moonshot AI · Meta · Updated for 2026

Which is better?

Kimi-k1.5 leads the overall LLM Stats Score 17.2 to -1.3, ranking #218 overall.

In the 3 individual benchmarks reported for both models, Kimi-k1.5 wins 3; 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 Kimi-k1.5

  • overall performance matters — it scores 17.2 and ranks #218 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • you want the most recent training data — it shipped Jan 2025

Choose Llama 3.2 11B Instruct

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

At a glance

The differences that matter most.

Core performance indexes
17.2
#218
-1.3
#334
16.4
#215
-0.8
#325
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
— / M
$0.05 / M
Output price
— / M
$0.05 / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Kimi-k1.5
Llama 3.2 11B Instruct
20.2#160
1.8#294
11.0#111
-0.3#182
14.7#92
2.4#147
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for Kimi-k1.5 · 11 for Llama 3.2 11B Instruct

3 shared

Kimi-k1.5 outperforms in 3 benchmarks (MathVista, MMLU, MMMU), while Llama 3.2 11B Instruct is better at 0 benchmarks.

Kimi-k1.5 significantly outperforms across most benchmarks.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Llama 3.2 11B Instruct specifies input context (128,000 tokens). Only Llama 3.2 11B Instruct specifies output context (128,000 tokens).

Moonshot AI
Kimi-k1.5
Input- tokens
Output- tokens
Meta
Llama 3.2 11B Instruct
Input128,000 tokens
Output128,000 tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Kimi-k1.5 and Llama 3.2 11B Instruct support multimodal inputs.

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

Kimi-k1.5

Text
Images
Audio
Video

Llama 3.2 11B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi-k1.5 is licensed under a proprietary license, while Llama 3.2 11B Instruct uses Llama 3.2 Community License.

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

Kimi-k1.5

Proprietary

Closed source

Llama 3.2 11B Instruct

Llama 3.2 Community License

Open weights

Release Timeline

When each model was launched

Kimi-k1.5 was released on 2025-01-20, while Llama 3.2 11B Instruct was released on 2024-09-25.

Kimi-k1.5 is 4 months newer than Llama 3.2 11B Instruct.

Kimi-k1.5

Jan 20, 2025

1.7 years ago

3mo newer
Llama 3.2 11B Instruct

Sep 25, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Llama 3.2 11B Instruct has a documented knowledge cutoff of 2023-12-31, while Kimi-k1.5's cutoff date is not specified.

We can confirm Llama 3.2 11B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without Kimi-k1.5's cutoff date.

Kimi-k1.5

Llama 3.2 11B Instruct

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Kimi-k1.5 and Llama 3.2 11B Instruct side-by-side, then vote on the output you prefer.

Kimi-k1.5
✓ Preferred
Llama 3.2 11B Instruct
Open in Playground

FAQ

Common questions about Kimi-k1.5 vs Llama 3.2 11B Instruct.

Which is better, Kimi-k1.5 or Llama 3.2 11B Instruct?

Kimi-k1.5 leads the LLM Stats Score 17.2 to -1.3. Kimi-k1.5 is made by Moonshot AI and Llama 3.2 11B Instruct is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Kimi-k1.5 compare to Llama 3.2 11B Instruct in benchmarks?

Kimi-k1.5 scores MATH-500: 96.2%, CLUEWSC: 91.4%, C-Eval: 88.3%, MMLU: 87.4%, IFEval: 87.2%. Llama 3.2 11B Instruct scores AI2D: 91.1%, DocVQA: 88.4%, ChartQA: 83.4%, VQAv2 (test): 75.2%, MMLU: 73.0%.

What are the context window sizes for Kimi-k1.5 and Llama 3.2 11B Instruct?

Kimi-k1.5 supports an unknown number of tokens and Llama 3.2 11B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Kimi-k1.5 and Llama 3.2 11B Instruct?

Key differences include LLM Stats Score (17.2 vs -1.3), licensing (Proprietary vs Llama 3.2 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi-k1.5 and Llama 3.2 11B Instruct?

Kimi-k1.5 is developed by Moonshot AI and Llama 3.2 11B Instruct is developed by Meta.