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DeepSeek-R1 vs Kimi K2.8 Preview

Comparing DeepSeek-R1 and Kimi K2.8 Preview across benchmarks, pricing, and capabilities.

DeepSeek · Moonshot AI · Updated for 2026

Which is better?

DeepSeek-R1 and Kimi K2.8 Preview trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Kimi K2.8 Preview 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-R1

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

Choose Kimi K2.8 Preview

  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.55 / M
— / M
Output price
$2.19 / M
— / M
Context window
131,072
1,048,576

Individual benchmarks

0 reported for DeepSeek-R1 · 0 for Kimi K2.8 Preview

No common benchmarks found

DeepSeek-R1 and Kimi K2.8 Previewdon'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 K2.8 Preview accepts 1,048,576 input tokens compared to DeepSeek-R1's 131,072 tokens. Only DeepSeek-R1 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Moonshot AI
Kimi K2.8 Preview
Input1,048,576 tokens
Output- tokens
Mon Sep 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Kimi K2.8 Preview supports multimodal inputs, whereas DeepSeek-R1 does not.

Kimi K2.8 Preview can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1

Text
Images
Audio
Video

Kimi K2.8 Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while Kimi K2.8 Preview uses a proprietary license.

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

DeepSeek-R1

MIT

Open weights

Kimi K2.8 Preview

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Kimi K2.8 Preview was released on 2026-09-11.

Kimi K2.8 Preview is 20 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.6 years ago

Kimi K2.8 Preview

Sep 11, 2026

3 days ago

1.6yr 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-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Kimi K2.8 Preview is available from Moonshot AI.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

Kimi K2.8 Preview

moonshot logo
Unknown Organization
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-R1 and Kimi K2.8 Preview side-by-side, then vote on the output you prefer.

DeepSeek-R1
✓ Preferred
Kimi K2.8 Preview
Open in Playground

FAQ

Common questions about DeepSeek-R1 vs Kimi K2.8 Preview.

Which is better, DeepSeek-R1 or Kimi K2.8 Preview?

DeepSeek-R1 (DeepSeek) and Kimi K2.8 Preview (Moonshot AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

What are the context window sizes for DeepSeek-R1 and Kimi K2.8 Preview?

DeepSeek-R1 supports 131K tokens and Kimi K2.8 Preview 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-R1 and Kimi K2.8 Preview?

Key differences include context window (131K vs 1.0M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1 and Kimi K2.8 Preview?

DeepSeek-R1 is developed by DeepSeek and Kimi K2.8 Preview is developed by Moonshot AI.