AI Flash Report

DeepSeek V3.2 vs Kimi K2: Benchmarks, Pricing & Capabilities Compared

TL;DR — DeepSeek V3.2 wins for general use · Kimi K2 wins for reasoning + cost + long-context.

DeepSeek V3.2 DeepSeek
Released
2026-02-12
Context window
1M tokens
Input price
$0.27 / Mtok
Output price
$1.10 / Mtok
Key features
  • 1M+ token context window (10x expansion)
  • Improved reasoning capabilities
  • Open source release
Kimi K2 Moonshot AI
Released
2026-01-20
Context window
2M tokens
Input price
$0.15 / Mtok
Output price
$2.50 / Mtok
Key features
  • First open-weight model #1 on LMSYS Chatbot Arena
  • 1.04 trillion parameters
  • K2.5 agent swarms with up to 100 sub-agents

Benchmark comparison

Benchmark DeepSeek V3.2 Kimi K2
LiveCodeBench 72.1% 68.9%
MMLU 90.1% 91.3%

Pricing comparison

Metric DeepSeek V3.2 Kimi K2
Input ($/Mtok) $0.27 $0.15
Output ($/Mtok) $1.10 $2.50
Cached input ($/Mtok) $0.07
Cost per 1M-token roundtrip (1M in + 1M out) $1.37 $2.65

Context window & modalities

Attribute DeepSeek V3.2 Kimi K2
Context window 1M tokens 2M tokens
Input modalities text text, image
Output modalities text text
Knowledge cutoff 2025-09 2025-10

Verdict by use case

Coding
→ DeepSeek V3.2
Basis: LiveCodeBench

DeepSeek V3.2 72.1% vs Kimi K2 68.9% on LiveCodeBench.

Reasoning
→ Kimi K2
Basis: GPQA Diamond

DeepSeek V3.2 68.4% vs Kimi K2 74.1% on GPQA Diamond.

Math
Insufficient data
Basis: MATH / AIME

No shared math benchmark.

Long context
→ Kimi K2
Basis: Context window

DeepSeek V3.2 1M tokens vs Kimi K2 2M tokens.

Cost
→ Kimi K2
Basis: Input $/Mtok

DeepSeek V3.2 $0.27/Mtok vs Kimi K2 $0.15/Mtok input.

Changelog & releases

DeepSeek V3.2
Released 2026-02-12
Predecessor: deepseek-deepseek-v3
  • 10x context window expansion (128K → 1M+ tokens)
  • Sliding-window attention for long-context throughput
  • Improved chain-of-thought reasoning
  • Native FP8 inference support
Kimi K2
Released 2026-01-20
  • 2M token context window (20x vs first Kimi)
  • Agentic tool-use tuning via MuonClip optimizer
  • Open weights under modified MIT

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