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DeepSeek VL2 vs Kimi K3.1 Pro

Kimi K3.1 Pro leads the LLM Stats Score 55.5 to 2.4.

DeepSeek · Moonshot AI · Updated for 2026

Which is better?

Kimi K3.1 Pro leads the overall LLM Stats Score 55.5 to 2.4, ranking #5 overall.

Kimi K3.1 Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose DeepSeek VL2

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

Choose Kimi K3.1 Pro

  • overall performance matters — it scores 55.5 and ranks #5 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

DeepSeek VL2
DeepSeek
Kimi K3.1 Pro
Moonshot AI
Core performance indexes
LLM Stats Score
2.4
#347
55.5
#5
Reasoning
-2.3
#366
54.3
#6
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$2.00 / M
Output price
— / M
$10.00 / M
Context window
129,280
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek VL2
Kimi K3.1 Pro
Vision
2.0#194
40.5#4
Multimodal
4.9#159
40.8#2
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek VL2 · 30 for Kimi K3.1 Pro

No common benchmarks found

DeepSeek VL2 and Kimi K3.1 Prodon'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

Context Window

Maximum input and output token capacity

Kimi K3.1 Pro accepts 1,048,576 input tokens compared to DeepSeek VL2's 129,280 tokens. Kimi K3.1 Pro can generate longer responses up to 1,048,576 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Moonshot AI
Kimi K3.1 Pro
Input1,048,576 tokens
Output1,048,576 tokens
Fri Oct 30 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek VL2 and Kimi K3.1 Pro support multimodal inputs.

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

DeepSeek VL2

Text
Images
Audio
Video

Kimi K3.1 Pro

Text
Images
Audio
Video

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Kimi K3.1 Pro was released on 2026-10-23.

Kimi K3.1 Pro is 23 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.9 years ago

Kimi K3.1 Pro

Oct 23, 2026

2 days ago

1.9yr 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

DeepSeek VL2 is available from Replicate. Kimi K3.1 Pro is available from Moonshot AI.

DeepSeek VL2

replicate logo
Replicate

Kimi K3.1 Pro

moonshot logo
Unknown Organization
Input Price:Input: $2.00/1MOutput Price:Output: $10.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek VL2 and Kimi K3.1 Pro side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Kimi K3.1 Pro
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs Kimi K3.1 Pro.

Which is better, DeepSeek VL2 or Kimi K3.1 Pro?

Kimi K3.1 Pro leads the LLM Stats Score 55.5 to 2.4. DeepSeek VL2 is made by DeepSeek and Kimi K3.1 Pro 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 K3.1 Pro in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Kimi K3.1 Pro scores BabyVision: 95.4%, GPQA: 94.2%, BenchCAD (with Python tool): 92.7%, BrowseComp: 92.1%, Chartography: 90.2%.

What are the context window sizes for DeepSeek VL2 and Kimi K3.1 Pro?

DeepSeek VL2 supports 129K tokens and Kimi K3.1 Pro supports 1.0M 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 K3.1 Pro?

Key differences include LLM Stats Score (2.4 vs 55.5), context window (129K vs 1.0M), licensing (deepseek vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Kimi K3.1 Pro?

DeepSeek VL2 is developed by DeepSeek and Kimi K3.1 Pro is developed by Moonshot AI.

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