Compare/K2-V2 (high) vs GPT-5.4 nano (medium)

K2-V2 (high)vsGPT-5.4 nano (medium)

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

MBZUAI Institute of Foundation Models

K2-V2 (high)

Input
$0/M
Output
$0/M
Speed
TTFT
OpenAI

GPT-5.4 nano (medium)

Input
$0.2/M
Output
$1.25/M
Speed
171 tok/s
TTFT
2.38s

Winner by Category

Cheaper
K2-V2 (high)
Faster (tok/s)
GPT-5.4 nano (medium)
Lower Latency
K2-V2 (high)
Benchmarks (4-7)
GPT-5.4 nano (medium)

Pricing Comparison

MetricK2-V2 (high)GPT-5.4 nano (medium)
Input ($/M tokens)$0$0.2
Output ($/M tokens)$0$1.25
Cost for 1M input + 100K output tokens:
K2-V2 (high)$0.00
GPT-5.4 nano (medium)$0.33

Speed Comparison

Output Speed (tokens/s) — higher is better
K2-V2 (high)
GPT-5.4 nano (medium)
171 tok/s
Time to First Token (seconds) — lower is better
K2-V2 (high)
GPT-5.4 nano (medium)
2.38s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
20.638.1
Coding Index
16.135.0
Math Index
78.3
GPQA Diamond
68.1%76.1%
MMLU-Pro
78.6%
LiveCodeBench
69.4%
AIME 2025
78.3%
MATH-500
Humanity's Last Exam
9.8%14.7%
SciCode
28.6%38.4%
IFBench
60.1%64.4%
TerminalBench
9.8%33.3%
K2-V2 (high)4 wins
7 winsGPT-5.4 nano (medium)

Frequently Asked Questions

Which is cheaper, K2-V2 (high) or GPT-5.4 nano (medium)?

K2-V2 (high) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.00/M tokens vs $0.46/M for GPT-5.4 nano (medium).

Which model performs better on benchmarks?

GPT-5.4 nano (medium) wins 7 out of 12 benchmarks compared to 4 for K2-V2 (high). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

GPT-5.4 nano (medium) generates tokens faster at 171 tok/s vs 0 tok/s. K2-V2 (high) also has lower time-to-first-token (0.00s vs 2.38s).

When should I use K2-V2 (high) vs GPT-5.4 nano (medium)?

Choose based on your priorities: K2-V2 (high) for lower cost, GPT-5.4 nano (medium) for stronger benchmark performance, and GPT-5.4 nano (medium) for faster generation. For latency-sensitive apps, check the TTFT comparison above.