Which is better: SWE-2 or Kimi K3?

Verdict: SWE-2 ranks higher (#22 vs #27) and wins 5 of 11 shared benchmarks; SWE-2 costs less ($0/$0 vs $3.00/$15.0 per 1M tokens). AskClash compares SWE-2 and Kimi K3 side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, AskClash ACB, and context window so you can see which model wins on each benchmark.

How do SWE-2 and Kimi K3 compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both SWE-2 and Kimi K3 when publicly disclosed.

LLM Comparison

SWE-2 vs Kimi K3: benchmark scores, pricing & comparison.

Side-by-side SWE-2 vs Kimi K3 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.

Verdict: SWE-2 ranks higher (#22 vs #27) and wins 5 of 11 shared benchmarks; SWE-2 costs less ($0/$0 vs $3.00/$15.0 per 1M tokens).

Open live leaderboard SWE-2 model page Kimi K3 model page

Rank #22 vs #27AskClash overall scores 55.3 vs 52.0.

Pricing $0/$0 vs $3.00/$15.0Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightCognition vs Moonshot AI.

SWE-2 vs Kimi K3 benchmark comparison

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

Metric	SWE-2	Kimi K3
Overall Score	55.3	52.0
Leaderboard Rank	#22	#27
ACB	60.0	57.7
RWT	8.5	8.0
Coding Agent Index	51.9	—
HLE	43.5	43.5
GPQA	93.5	93.5
SWE-Atlas	66.1	—
Terminal-Bench	27.3	12.6
DeepSWE	73.0	68.5
GDPval-AA	1668.0	1668.0
MCP Atlas	84.2	84.2
Finance Agent	54.4	53.1
CharXiv	84.8	84.8
MMMU-Pro	81.6	81.6
Input Price (per 1M tokens)	$0	$3.00
Output Price (per 1M tokens)	$0	$15.0
Context Window	256K	1M
Benchmarks Published	13	11

SWE-2 vs Kimi K3 head-to-head charts

SWE-2 leads 6 and Kimi K3 leads 0 of 12 shared benchmarks. SWE-2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

SWE-2Kimi K3

Overall

55.3SWE-2

52.0Kimi K3

ACB

60.0SWE-2

57.7Kimi K3

RWT

8.5SWE-2

8.0Kimi K3

HLE

43.5SWE-2

43.5Kimi K3

GPQA

93.5SWE-2

93.5Kimi K3

Terminal-Bench

27.3SWE-2

12.6Kimi K3

DeepSWE

73.0SWE-2

68.5Kimi K3

GDPval-AA

1668.0SWE-2

1668.0Kimi K3

MCP Atlas

84.2SWE-2

84.2Kimi K3

Finance Agent

54.4SWE-2

53.1Kimi K3

CharXiv

84.8SWE-2

84.8Kimi K3

MMMU-Pro

81.6SWE-2

81.6Kimi K3

SWE-2

Input$0

Output$0

Workload$0.00

Context256K

Kimi K3

Input$3.00

Output$15.0

Workload$6.00

Context1M

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

More SWE-2 and Kimi K3 comparisons

Explore how SWE-2 and Kimi K3 stack up against other top-ranked LLMs.

Claude Opus 5.5 vs SWE-2 Claude Opus 5.5 vs Kimi K3 Claude Sonnet 5.5 vs SWE-2 Claude Sonnet 5.5 vs Kimi K3 Claude Fable 5.1 vs SWE-2 Claude Fable 5.1 vs Kimi K3 Claude Opus 5 vs SWE-2 Claude Opus 5 vs Kimi K3 Claude Fable 5 vs SWE-2 Claude Fable 5 vs Kimi K3

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.