LLM Comparison

Kimi K3 vs DeepSeek V4 Pro 0813: benchmark scores, pricing & comparison.

Side-by-side Kimi K3 vs DeepSeek V4 Pro 0813 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Rank #4 vs #17AskClash overall scores 77.3 vs 60.5.
Pricing $3.00/$15.0 vs $0.43/$0.87Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightMoonshot AI vs DeepSeek.

Kimi K3 vs DeepSeek V4 Pro 0813 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricKimi K3DeepSeek V4 Pro 0813
Overall Score77.360.5
Leaderboard Rank#4#17
RWT8.07.0
HLE43.542.7
GPQA93.590.1
SWE-bench80.6
SWE-Pro55.4
Terminal-Bench88.387.9
DeepSWE68.562.7
MCP Atlas84.273.6
Finance Agent54.4
CharXiv84.8
MMMU-Pro81.6
Input Price (per 1M tokens)$3.00$0.43
Output Price (per 1M tokens)$15.0$0.87
Context Window1M1M
Benchmarks Published119

Kimi K3 vs DeepSeek V4 Pro 0813 head-to-head charts

Kimi K3 leads 7 and DeepSeek V4 Pro 0813 leads 0 of 7 shared benchmarks. DeepSeek V4 Pro 0813 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Kimi K3DeepSeek V4 Pro 0813
Overall
77.3Kimi K3
60.5DeepSeek V4 Pro 0813
RWT
8.0Kimi K3
7.0DeepSeek V4 Pro 0813
HLE
43.5Kimi K3
42.7DeepSeek V4 Pro 0813
GPQA
93.5Kimi K3
90.1DeepSeek V4 Pro 0813
Terminal-Bench
88.3Kimi K3
87.9DeepSeek V4 Pro 0813
DeepSWE
68.5Kimi K3
62.7DeepSeek V4 Pro 0813
MCP Atlas
84.2Kimi K3
73.6DeepSeek V4 Pro 0813
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M
DeepSeek V4 Pro 0813
Input$0.43
Output$0.87
Workload$0.61
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More Kimi K3 and DeepSeek V4 Pro 0813 comparisons

Explore how Kimi K3 and DeepSeek V4 Pro 0813 stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.