Nova Pro vs Kimi K2 Thinking

Comparing 2 AI models · 6 benchmarks · Amazon, Moonshot AI

Most Affordable
Moonshot AI logo
Kimi K2 Thinking
$0.60/1M
Highest Intelligence
Moonshot AI logo
Kimi K2 Thinking
83.8% GPQA
Best for Coding
Moonshot AI logo
Kimi K2 Thinking
52.2 Coding Index
Price Difference
1.3x
input cost range

Composite Indices

Intelligence, Coding, Math

Standard Benchmarks

Academic and industry benchmarks

Benchmark Winners

6 tests
Amazon logo

Nova Pro

1
  • MATH 500
Moonshot AI logo

Kimi K2 Thinking

5
  • GPQA
  • MMLU Pro
  • HLE
  • LiveCodeBench
  • AIME 2025
Metric
Amazon logo Nova Pro
Amazon
Moonshot AI logo Kimi K2 Thinking
Moonshot AI
Pricing
Per 1M tokens
Input Cost $0.80/1M $0.60/1M
Output Cost $3.20/1M $2.50/1M
Blended Cost 3:1 input/output ratio
$1.40/1M $1.07/1M
Specifications
Organization Model creator
Amazon Moonshot AI
Release Date Launch date
Dec 3, 2024 Nov 6, 2025
Performance & Speed
Throughput Output speed
79.9 tok/s
Time to First Token (TTFT) Initial response delay
821ms
Latency Time to first answer token
25848ms
Composite Indices
Intelligence Index Overall reasoning capability
25.0 67.0
Coding Index Programming ability
16.6 52.2
Math Index Mathematical reasoning
7.0 94.7
Standard Benchmarks
GPQA Graduate-level reasoning
49.9% 83.8%
MMLU Pro Advanced knowledge
69.1% 84.8%
HLE Hard language evaluation
3.4% 22.3%
LiveCodeBench Real-world coding tasks
23.3% 85.3%
MATH 500 Mathematical problems
78.6%
AIME 2025 Advanced math competition
7.0% 94.7%
AIME (Original) Math olympiad problems
10.7%
SciCode Scientific code generation
20.8% 42.4%
LCR Code review capability
19.0% 66.3%
IFBench Instruction-following
38.1% 68.1%
TAU-bench v2 Tool use & agentic tasks
14.0% 93.0%
TerminalBench Hard CLI command generation
5.7% 29.1%

Key Takeaways

Kimi K2 Thinking offers the best value at $0.60/1M, making it ideal for high-volume applications and cost-conscious projects.

Kimi K2 Thinking leads in reasoning capabilities with a 83.8% GPQA score, excelling at complex analytical tasks and problem-solving.

Kimi K2 Thinking achieves a 52.2 coding index, making it the top choice for software development and code generation tasks.

All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.

When to Choose Each Model

Amazon logo

Nova Pro

  • General-purpose AI
  • Versatile applications
Moonshot AI logo

Kimi K2 Thinking

  • Cost-sensitive applications
  • High-volume processing
  • Complex reasoning tasks
  • Research & analysis
  • Code generation
  • Software development

Cost Calculator

Amazon logo Nova Pro
$0.00
per month
Moonshot AI logo Kimi K2 Thinking
$0.00
per month

Costs are estimates based on API pricing. Actual costs may vary based on caching, batch processing, and volume discounts.

AI Model Comparison Guide

Compare large language models (LLMs) side-by-side with detailed benchmark scores, pricing, and performance metrics. Our interactive comparison tool helps you evaluate AI models from OpenAI, Anthropic, Google, Meta, DeepSeek, and other leading providers. Use our AI model leaderboard to discover more models to compare.

Understanding Composite Indices

  • Intelligence Index: Aggregated score combining MMLU-Pro, GPQA, and HLE benchmarks - measures overall reasoning and knowledge capabilities
  • Coding Index: Composite metric from LiveCodeBench, SciCode, and LiveCodeBench Review - evaluates programming proficiency across multiple languages
  • Math Index: Combined score from AIME, AIME 2025, and MATH-500 benchmarks - assesses mathematical reasoning from high school to competition level

Key Comparison Metrics

  • Benchmark Scores: Standardized tests measuring intelligence, coding, math, and specialized capabilities - higher percentages indicate better performance
  • Pricing Analysis: Compare input and output token costs across models - critical for budgeting API usage and scaling applications
  • Performance Metrics: Throughput (tokens/second) and latency measurements for real-time application planning
  • Context Windows: Maximum token capacity for processing documents and maintaining conversation history

How to Compare AI Models Effectively

Performance vs Cost

Balance benchmark scores against token pricing - flagship models offer 10-15% better performance but cost 5-10x more than smaller alternatives

Task-Specific Selection

Prioritize relevant indices: coding index for development tasks, math index for STEM applications, intelligence index for general reasoning

Real-World Testing

Use our free AI chat interface to test models with your specific prompts before committing to API integration

All benchmark scores, pricing data, and performance metrics are sourced from Artificial Analysis and updated daily. Compare models by intelligence, coding ability, math performance, speed, cost, or release date using our comprehensive AI model leaderboard.