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DeepSeek-V4-Pro-0813 vs Kimi K2 Base

Comparing DeepSeek-V4-Pro-0813 and Kimi K2 Base across benchmarks, pricing, and capabilities.

DeepSeek · Moonshot AI · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 and Kimi K2 Base trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Pro-0813

  • you want the most recent training data — it shipped Aug 2026

Choose Kimi K2 Base

  • you are already invested in the Moonshot AI ecosystem

At a glance

The differences that matter most.

DeepSeek-V4-Pro-0813
DeepSeek
Kimi K2 Base
Moonshot AI
Benchmark wins
—
—
Input price
$0.43 / M
— / M
Output price
$0.87 / M
— / M
Context window
1,048,576
—
Released
Aug 2026
Jul 2025
License
MIT
MIT

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Pro-0813 and Kimi K2 Basedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

600.0B diff

DeepSeek-V4-Pro-0813 has 600.0B more parameters than Kimi K2 Base, making it 60.0% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
Moonshot AI
Kimi K2 Base
1.0Tparameters
1600.0B
DeepSeek-V4-Pro-0813
1000.0B
Kimi K2 Base

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output393,216 tokens
Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V4-Pro-0813

MIT

Open weights

Kimi K2 Base

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Kimi K2 Base was released on 2025-07-11.

DeepSeek-V4-Pro-0813 is 13 months newer than Kimi K2 Base.

DeepSeek-V4-Pro-0813

Aug 13, 2026

1 weeks ago

1.1yr newer
Kimi K2 Base

Jul 11, 2025

1.1 years ago

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-V4-Pro-0813 and Kimi K2 Base side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
Kimi K2 Base
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs Kimi K2 Base.

Which is better, DeepSeek-V4-Pro-0813 or Kimi K2 Base?

DeepSeek-V4-Pro-0813 (DeepSeek) and Kimi K2 Base (Moonshot AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V4-Pro-0813 compare to Kimi K2 Base in benchmarks?

DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%. 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-V4-Pro-0813 and Kimi K2 Base?

DeepSeek-V4-Pro-0813 supports 1.0M 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.

Who makes DeepSeek-V4-Pro-0813 and Kimi K2 Base?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and Kimi K2 Base is developed by Moonshot AI.

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