Model Comparison

DeepSeek-V3.2-Exp vs Kimi K2 Instruct

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is 1.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

DeepSeek-V3.2-Exp outperforms in 9 benchmarks (Aider-Polyglot, AIME 2025, GPQA, HMMT 2025, Humanity's Last Exam, MMLU-Pro, SimpleQA, SWE-bench Multilingual, Terminal-Bench), while Kimi K2 Instruct is better at 0 benchmarks.

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Sat May 02 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2-Exp costs less

For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 1.9x cheaper than Kimi K2 Instruct ($0.50/1M tokens).

For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 1.2x cheaper than Kimi K2 Instruct ($0.50/1M tokens).

In conclusion, Kimi K2 Instruct is more expensive than DeepSeek-V3.2-Exp.*

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

Lowest available price from all providers
Sat May 02 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Moonshot AI
Kimi K2 Instruct
Input tokens$0.50
Output tokens$0.50
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

315.0B diff

Kimi K2 Instruct has 315.0B more parameters than DeepSeek-V3.2-Exp, making it 46.0% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Moonshot AI
Kimi K2 Instruct
1000.0Bparameters
685.0B
DeepSeek-V3.2-Exp
1000.0B
Kimi K2 Instruct

Context Window

Maximum input and output token capacity

Kimi K2 Instruct accepts 200,000 input tokens compared to DeepSeek-V3.2-Exp's 163,840 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Moonshot AI
Kimi K2 Instruct
Input200,000 tokens
Output200,000 tokens
Sat May 02 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-V3.2-Exp

MIT

Open weights

Kimi K2 Instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Kimi K2 Instruct was released on 2025-07-11.

DeepSeek-V3.2-Exp is 3 months newer than Kimi K2 Instruct.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

2mo newer
Kimi K2 Instruct

Jul 11, 2025

9 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-Exp is available from Novita. Kimi K2 Instruct is available from Fireworks, Novita.

DeepSeek-V3.2-Exp

novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $0.41/1M

Kimi K2 Instruct

fireworks logo
Fireworks
Input Price:Input: $0.50/1MOutput Price:Output: $0.50/1M
novita logo
Novita
Input Price:Input: $0.57/1MOutput Price:Output: $2.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Higher Aider-Polyglot score (74.5% vs 60.0%)
Higher AIME 2025 score (89.3% vs 49.5%)
Higher GPQA score (79.9% vs 75.1%)
Higher HMMT 2025 score (83.6% vs 38.8%)
Higher Humanity's Last Exam score (19.8% vs 4.7%)
Higher MMLU-Pro score (85.0% vs 81.1%)
Higher SimpleQA score (97.1% vs 31.0%)
Higher SWE-bench Multilingual score (57.9% vs 47.3%)
Higher Terminal-Bench score (37.7% vs 30.0%)
Moonshot AI
Larger context window (200,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Moonshot AI
Kimi K2 Instruct

FAQ

Common questions about DeepSeek-V3.2-Exp vs Kimi K2 Instruct

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and Kimi K2 Instruct is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%.
DeepSeek-V3.2-Exp is 1.9x cheaper for input tokens. DeepSeek-V3.2-Exp costs $0.27/M input and $0.41/M output via novita. Kimi K2 Instruct costs $0.50/M input and $0.50/M output via fireworks.
DeepSeek-V3.2-Exp supports 164K tokens and Kimi K2 Instruct supports 200K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (164K vs 200K), input pricing ($0.27 vs $0.50/M). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Kimi K2 Instruct is developed by Moonshot AI.