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DeepSeek VL2 vs Kimi K2 Base

Kimi K2 Base leads the LLM Stats Score 13.6 to 3.1.

DeepSeek · Moonshot AI · Updated for 2026

Which is better?

Kimi K2 Base leads the overall LLM Stats Score 13.6 to 3.1, ranking #233 overall.

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

Choose DeepSeek VL2

  • you are already invested in the DeepSeek ecosystem

Choose Kimi K2 Base

  • overall performance matters — it scores 13.6 and ranks #233 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jul 2025

At a glance

The differences that matter most.

Core performance indexes
3.1
#299
13.6
#233
-1.5
#316
12.8
#231
Cost, coverage & limits
Benchmark wins
Input price
— / M
— / M
Output price
— / M
— / M
Context window
129,280

Individual benchmarks

14 reported for DeepSeek VL2 · 13 for Kimi K2 Base

No common benchmarks found

DeepSeek VL2 and Kimi K2 Basedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

973.0B diff

Kimi K2 Base has 973.0B more parameters than DeepSeek VL2, making it 3603.7% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Moonshot AI
Kimi K2 Base
1.0Tparameters
27.0B
DeepSeek VL2
1000.0B
Kimi K2 Base

Context Window

Maximum input and output token capacity

Only DeepSeek VL2 specifies input context (129,280 tokens). Only DeepSeek VL2 specifies output context (129,280 tokens).

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek VL2 supports multimodal inputs, whereas Kimi K2 Base does not.

DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2

Text
Images
Audio
Video

Kimi K2 Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Kimi K2 Base uses MIT.

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

DeepSeek VL2

deepseek

Open weights

Kimi K2 Base

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Kimi K2 Base was released on 2025-07-11.

Kimi K2 Base is 7 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.7 years ago

Kimi K2 Base

Jul 11, 2025

1.2 years ago

7mo 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

Judge for yourself.

Run your own prompts against DeepSeek VL2 and Kimi K2 Base side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Kimi K2 Base
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs Kimi K2 Base.

Which is better, DeepSeek VL2 or Kimi K2 Base?

Kimi K2 Base leads the LLM Stats Score 13.6 to 3.1. DeepSeek VL2 is made by DeepSeek and Kimi K2 Base 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 DeepSeek VL2 compare to Kimi K2 Base in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Kimi K2 Base scores C-Eval: 92.5%, GSM8k: 92.1%, MMLU-redux-2.0: 90.2%, MMLU: 87.8%, TriviaQA: 85.1%.

What are the context window sizes for DeepSeek VL2 and Kimi K2 Base?

DeepSeek VL2 supports 129K tokens and Kimi K2 Base 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 DeepSeek VL2 and Kimi K2 Base?

Key differences include LLM Stats Score (3.1 vs 13.6), multimodal support (yes vs no), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Kimi K2 Base?

DeepSeek VL2 is developed by DeepSeek and Kimi K2 Base is developed by Moonshot AI.