How do Kimi K2.7 and DeepSeek V4 Pro (Max) compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both Kimi K2.7 and DeepSeek V4 Pro (Max) when publicly disclosed.

LLM Comparison

Kimi K2.7 vs DeepSeek V4 Pro (Max): benchmark scores, pricing & comparison.

Q: Which is better: Kimi K2.7 or DeepSeek V4 Pro (Max)?

AskClash compares Kimi K2.7 and DeepSeek V4 Pro (Max) side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, and context window so you can see which model wins on each benchmark.

Side-by-side Kimi K2.7 vs DeepSeek V4 Pro (Max) 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.

Open live leaderboard Kimi K2.7 model page DeepSeek V4 Pro (Max) model page

Rank #18 vs #27AskClash overall scores 57.1 vs 48.7.

Pricing $0.95/$4.00 vs $0.43/$0.87Input and output token prices per 1M tokens when published.

Open Weight vs Open WeightMoonshot AI vs DeepSeek.

Kimi K2.7 vs DeepSeek V4 Pro (Max) benchmark comparison

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

Metric	Kimi K2.7	DeepSeek V4 Pro (Max)
Overall Score	57.1	48.7
Leaderboard Rank	#18	#27
RWT	7.5	7.0
HLE	54.0	37.7
GPQA	90.5	90.1
MATH-500	—	64.5
SWE-bench	80.2	80.6
SWE-Pro	58.6	55.4
Terminal-Bench	66.7	67.9
DeepSWE	30.5	—
OSWorld	73.1	—
MCP Atlas	76.0	73.6
Finance Agent	44.9	—
CharXiv	80.4	—
MMMU-Pro	79.4	—
Tau2	90.1	96.2
MRCR	—	83.5
Input Price (per 1M tokens)	$0.95	$0.43
Output Price (per 1M tokens)	$4.00	$0.87
Context Window	256K	1M
Benchmarks Published	13	9

Kimi K2.7 vs DeepSeek V4 Pro (Max) head-to-head charts

Kimi K2.7 leads 6 and DeepSeek V4 Pro (Max) leads 3 of 9 shared benchmarks. DeepSeek V4 Pro (Max) is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Kimi K2.7DeepSeek V4 Pro (Max)

Overall

57.1Kimi K2.7

48.7DeepSeek V4 Pro (Max)

RWT

7.5Kimi K2.7

7.0DeepSeek V4 Pro (Max)

HLE

54.0Kimi K2.7

37.7DeepSeek V4 Pro (Max)

GPQA

90.5Kimi K2.7

90.1DeepSeek V4 Pro (Max)

SWE-bench

80.2Kimi K2.7

80.6DeepSeek V4 Pro (Max)

SWE-Pro

58.6Kimi K2.7

55.4DeepSeek V4 Pro (Max)

Terminal-Bench

66.7Kimi K2.7

67.9DeepSeek V4 Pro (Max)

MCP Atlas

76.0Kimi K2.7

73.6DeepSeek V4 Pro (Max)

Tau2

90.1Kimi K2.7

96.2DeepSeek V4 Pro (Max)

Kimi K2.7

Input$0.95

Output$4.00

Workload$1.75

Context256K

DeepSeek V4 Pro (Max)

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.

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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.