DeepSeek-V3.2 (Thinking) vs Kimi K2 0905 Comparison

Comparing DeepSeek-V3.2 (Thinking) and Kimi K2 0905 across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Kimi K2 0905 is better at 0 benchmarks.

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

Tue Mar 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 (Thinking) costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 2.1x cheaper than Kimi K2 0905 ($0.60/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 6.0x cheaper than Kimi K2 0905 ($2.50/1M tokens).

In conclusion, Kimi K2 0905 is more expensive than DeepSeek-V3.2 (Thinking).*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Mar 17 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Moonshot AI
Kimi K2 0905
Input tokens$0.60
Output tokens$2.50
Best providerNovita
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

315.0B diff

Kimi K2 0905 has 315.0B more parameters than DeepSeek-V3.2 (Thinking), making it 46.0% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
Moonshot AI
Kimi K2 0905
1000.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
1000.0B
Kimi K2 0905

Context Window

Maximum input and output token capacity

Kimi K2 0905 accepts 262,144 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. Kimi K2 0905 can generate longer responses up to 262,144 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Moonshot AI
Kimi K2 0905
Input262,144 tokens
Output262,144 tokens
Tue Mar 17 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while Kimi K2 0905 uses a proprietary license.

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

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Kimi K2 0905

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Kimi K2 0905 was released on 2025-09-05.

DeepSeek-V3.2 (Thinking) is 3 months newer than Kimi K2 0905.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

3 months ago

2mo newer
Kimi K2 0905

Sep 5, 2025

6 months 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

Provider Availability

DeepSeek-V3.2 (Thinking) is available from DeepSeek. Kimi K2 0905 is available from Novita. The availability of providers can affect quality of the model and reliability.

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Kimi K2 0905

novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (82.4% vs 75.8%)
Higher MMLU-Pro score (85.0% vs 82.5%)
Larger context window (262,144 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Thinking)
Moonshot AI
Kimi K2 0905