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DeepSeek

DeepSeek V4 Pro

VS
Moonshot AI (Kimi)

kimi-k2.5

✍️ Analysis by:the whichllmmodel Editorial Team|📅 Updated: June 2026

Decision Recommendation

⚖️ Editorial Verdict: In our analysis, DeepSeek V4 Pro is the premium intelligence choice, scoring 1.4% higher on coding benchmarks. However, this accuracy premium comes with a cost overhead: kimi-k2.5 is 1.8x cheaper to run and delivers 4.9x faster throughput. If you are building high-volume, simple chatbots or processing massive amounts of text where budget is critical, kimi-k2.5 offers excellent cost savings. For agentic reasoning, code refactoring, or complex logical tasks, the accuracy premium of DeepSeek V4 Pro fully justifies the cost.

Model Specs

DeepSeek V4 Pro

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+1.4%)
52.1%
Reasoning (gpqa-diamond)Winner (+0.4%)
88%

Cost & Performance

Cost (per 1M tokens)
$2.17Input: $1.74 | Output: $3.48
Speed
39.7 tps
Context WindowLarger
1M tokens
Model Specs

kimi-k2.5

Benchmarks & Scores

Coding (swe-bench-pro)
50.7%
Reasoning (gpqa-diamond)
87.6%

Cost & Performance

Cost (per 1M tokens)1.8x cheaper
$1.20Input: $0.60 | Output: $3.00
Speed4.9x faster
193 tps
Context Window
262.14k tokens
Read our data collection methodology

Frequently Asked Questions

kimi-k2.5 is cheaper than DeepSeek V4 Pro. kimi-k2.5 has a blended cost of $1.20/1M tokens, which is about 1.8x cheaper than DeepSeek V4 Pro at $2.17/1M tokens.

kimi-k2.5 is faster than DeepSeek V4 Pro. kimi-k2.5 generates 193 tokens per second (tps) compared to DeepSeek V4 Pro which generates 39.7 tokens per second.

DeepSeek V4 Pro is better for coding tasks. It scores 52.1% on coding evaluations (swe-bench-pro) compared to kimi-k2.5 which scores 50.7%.

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