LLM Comparison

Kimi K3 vs DeepSeek V4 Flash 0731: benchmark scores, pricing & comparison.

Side-by-side Kimi K3 vs DeepSeek V4 Flash 0731 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 #16AskClash overall scores 76.8 vs 56.1.
Pricing $3.00/$15.0 vs $0.14/$0.28Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightMoonshot AI vs DeepSeek.

Kimi K3 vs DeepSeek V4 Flash 0731 benchmark comparison

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

MetricKimi K3DeepSeek V4 Flash 0731
Overall Score76.856.1
Leaderboard Rank#4#16
RWT8.0
HLE43.537.0
GPQA93.591.0
MATH-50057.4
SWE-bench79.0
Terminal-Bench88.382.7
DeepSWE68.554.4
MCP Atlas84.269.0
Finance Agent54.4
CharXiv84.8
MMMU-Pro81.6
MRCR78.7
Input Price (per 1M tokens)$3.00$0.14
Output Price (per 1M tokens)$15.0$0.28
Context Window1M1M
Benchmarks Published119

Kimi K3 vs DeepSeek V4 Flash 0731 head-to-head charts

Kimi K3 leads 6 and DeepSeek V4 Flash 0731 leads 0 of 6 shared benchmarks. DeepSeek V4 Flash 0731 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Kimi K3DeepSeek V4 Flash 0731
Overall
76.8Kimi K3
56.1DeepSeek V4 Flash 0731
HLE
43.5Kimi K3
37.0DeepSeek V4 Flash 0731
GPQA
93.5Kimi K3
91.0DeepSeek V4 Flash 0731
Terminal-Bench
88.3Kimi K3
82.7DeepSeek V4 Flash 0731
DeepSWE
68.5Kimi K3
54.4DeepSeek V4 Flash 0731
MCP Atlas
84.2Kimi K3
69.0DeepSeek V4 Flash 0731
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M
DeepSeek V4 Flash 0731
Input$0.14
Output$0.28
Workload$0.20
Context1M

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

More Kimi K3 and DeepSeek V4 Flash 0731 comparisons

Explore how Kimi K3 and DeepSeek V4 Flash 0731 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.