Compare/Nova 2.0 Omni (low) vs Kimi K2 Thinking

Nova 2.0 Omni (low)vsKimi K2 Thinking

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Amazon

Nova 2.0 Omni (low)

Input
$0.3/M
Output
$2.5/M
Speed
TTFT
Kimi

Kimi K2 Thinking

Input
$0.6/M
Output
$2.5/M
Speed
103 tok/s
TTFT
0.66s

Winner by Category

Cheaper
Nova 2.0 Omni (low)
Faster (tok/s)
Kimi K2 Thinking
Lower Latency
Nova 2.0 Omni (low)
Benchmarks (0-11)
Kimi K2 Thinking

Pricing Comparison

MetricNova 2.0 Omni (low)Kimi K2 Thinking
Input ($/M tokens)$0.3$0.6
Output ($/M tokens)$2.5$2.5
Cost for 1M input + 100K output tokens:
Nova 2.0 Omni (low)$0.55
Kimi K2 Thinking$0.85

Speed Comparison

Output Speed (tokens/s) — higher is better
Nova 2.0 Omni (low)
Kimi K2 Thinking
103 tok/s
Time to First Token (seconds) — lower is better
Nova 2.0 Omni (low)
Kimi K2 Thinking
0.66s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
23.240.9
Coding Index
13.934.8
Math Index
56.094.7
GPQA Diamond
69.9%83.8%
MMLU-Pro
79.8%84.8%
LiveCodeBench
59.2%85.3%
AIME 2025
56.0%94.7%
MATH-500
Humanity's Last Exam
4.0%22.3%
SciCode
34.3%42.4%
IFBench
61.8%68.1%
TerminalBench
3.8%31.1%
Nova 2.0 Omni (low)0 wins
11 winsKimi K2 Thinking

Frequently Asked Questions

Which is cheaper, Nova 2.0 Omni (low) or Kimi K2 Thinking?

Nova 2.0 Omni (low) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.85/M tokens vs $1.07/M for Kimi K2 Thinking.

Which model performs better on benchmarks?

Kimi K2 Thinking wins 11 out of 12 benchmarks compared to 0 for Nova 2.0 Omni (low). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Kimi K2 Thinking generates tokens faster at 103 tok/s vs 0 tok/s. Nova 2.0 Omni (low) also has lower time-to-first-token (0.00s vs 0.66s).

When should I use Nova 2.0 Omni (low) vs Kimi K2 Thinking?

Choose based on your priorities: Nova 2.0 Omni (low) for lower cost, Kimi K2 Thinking for stronger benchmark performance, and Kimi K2 Thinking for faster generation. For latency-sensitive apps, check the TTFT comparison above.