LLM Comparison

GPT-5.6 Terra vs Kimi K2.7: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Terra vs Kimi K2.7 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 #8 vs #19AskClash overall scores 76.3 vs 56.8.
Pricing $2.50/$15.0 vs $0.95/$4.00Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightOpenAI vs Moonshot AI.

GPT-5.6 Terra vs Kimi K2.7 benchmark comparison

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

MetricGPT-5.6 TerraKimi K2.7
Overall Score76.356.8
Leaderboard Rank#8#19
RWT8.57.5
Coding Agent Index77.0
HLE54.0
GPQA92.990.5
SWE-bench80.2
SWE-Pro63.458.6
SWE-Atlas81.0
Terminal-Bench87.466.7
DeepSWE69.630.5
OSWorld73.1
MCP Atlas76.0
Finance Agent52.444.9
CharXiv80.4
MMMU-Pro80.779.4
ARC-AGI 283.9
Tau286.390.1
MRCR89.6
Input Price (per 1M tokens)$2.50$0.95
Output Price (per 1M tokens)$15.0$4.00
Context Window1M256K
Benchmarks Published1313

GPT-5.6 Terra vs Kimi K2.7 head-to-head charts

GPT-5.6 Terra leads 8 and Kimi K2.7 leads 1 of 9 shared benchmarks. Kimi K2.7 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 TerraKimi K2.7
Overall
76.3GPT-5.6 Terra
56.8Kimi K2.7
RWT
8.5GPT-5.6 Terra
7.5Kimi K2.7
GPQA
92.9GPT-5.6 Terra
90.5Kimi K2.7
SWE-Pro
63.4GPT-5.6 Terra
58.6Kimi K2.7
Terminal-Bench
87.4GPT-5.6 Terra
66.7Kimi K2.7
DeepSWE
69.6GPT-5.6 Terra
30.5Kimi K2.7
Finance Agent
52.4GPT-5.6 Terra
44.9Kimi K2.7
MMMU-Pro
80.7GPT-5.6 Terra
79.4Kimi K2.7
Tau2
86.3GPT-5.6 Terra
90.1Kimi K2.7
GPT-5.6 Terra
Input$2.50
Output$15.0
Workload$5.50
Context1M
Kimi K2.7
Input$0.95
Output$4.00
Workload$1.75
Context256K

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

More GPT-5.6 Terra and Kimi K2.7 comparisons

Explore how GPT-5.6 Terra and Kimi K2.7 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.