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.

Rank #10 vs #17AskClash overall scores 66.3 vs 63.9.
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.

MetricSWE-2Kimi K3
Overall Score66.363.9
Leaderboard Rank#10#17
ACB60.057.7
RWT8.58.0
Coding Agent Index51.951.9
HLE43.543.5
GPQA93.593.5
SWE-Atlas66.166.1
Terminal-Bench92.888.3
DeepSWE73.068.5
GDPval-AA1668.01668.0
MCP Atlas84.284.2
Finance Agent54.454.4
CharXiv84.884.8
MMMU-Pro81.681.6
Input Price (per 1M tokens)$0$3.00
Output Price (per 1M tokens)$0$15.0
Context Window256K1M
Benchmarks Published1313

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

SWE-2 leads 5 and Kimi K3 leads 0 of 14 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
66.3SWE-2
63.9Kimi K3
ACB
60.0SWE-2
57.7Kimi K3
RWT
8.5SWE-2
8.0Kimi K3
Coding Agent Index
51.9SWE-2
51.9Kimi K3
HLE
43.5SWE-2
43.5Kimi K3
GPQA
93.5SWE-2
93.5Kimi K3
SWE-Atlas
66.1SWE-2
66.1Kimi K3
Terminal-Bench
92.8SWE-2
88.3Kimi 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
54.4Kimi 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.

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.