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Model comparison

GLM-5.2 vs Kimi K2.7 Code

Data verified

Head-to-head evidence from 19 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

63.96/100
Margin
9.0pts
← winning
Kimi K2.7 Code
Moonshot AI
55/100
0 category wins0 category wins

Public leaderboard positions: GLM-5.2 #37 (Estimated); Kimi K2.7 Code #87 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-5.2 and Kimi K2.7 Code share 19 comparable benchmark results. 0 of 8 categories are comparable. 24 results are unique to GLM-5.2; 4 to Kimi K2.7 Code.

Updated July 23, 2026
Shared results
19
GLM-5.2 only
24
Kimi K2.7 Code only
4
Comparable categories
0 / 8

Benchmark data for GLM-5.2 and Kimi K2.7 Code is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 19 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

GLM-5.2 is priced at $1.40 input / $4.40 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.7 Code. GLM-5.2 has the larger context window at 1M, compared with 256K for Kimi K2.7 Code.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for GLM-5.2 and Kimi K2.7 Code
CategoryGLM-5.2ΔKimi K2.7 Code
AgenticGLM-5.281.0MarginNo overlapKimi K2.7 CodeNot measured
CodingGLM-5.262.1MarginNo overlapKimi K2.7 CodeNot measured
KnowledgeGLM-5.259.6MarginNo overlapKimi K2.7 CodeNot measured
MathGLM-5.295.9MarginNo overlapKimi K2.7 CodeNot measured

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGLM-5.2Kimi K2.7 CodeComparison
Input / output priceUSD per 1M tokensGLM-5.2$1.4 input / $4.4 outputKimi K2.7 Code$0.95 input / $4 outputKimi K2.7 Code has the lower combined listed price.
Generation speedtokens per secondGLM-5.2Not availableKimi K2.7 CodeNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-5.2Not availableKimi K2.7 CodeNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-5.21MKimi K2.7 Code256KGLM-5.2 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-5.2Kimi K2.7 CodeResult
Terminal-Bench 2.0Source 81%—Not comparable
MCP AtlasSource 76.8%76%GLM-5.2 leads
ToolathlonSource 48.2%—Not comparable
AA Agentic IndexSource 43.1%29.6%GLM-5.2 leads
τ²-bench resultsSource 99.1%90.1%GLM-5.2 leads
GDPval-AASource 50.7%34.3%GLM-5.2 leads
GDPval-AASource 15141187GLM-5.2 leads
APEX-Agents-AASource 33.7%—Not comparable
ResearchClawBenchSource 20.7%—Not comparable
AA BriefcaseSource 1260—Not comparable
AA AutomationBenchSource 27.8%—Not comparable
AA EnterpriseOps-GymSource 42.7%—Not comparable
AA Harvey LABSource 91.0%—Not comparable
AA ITBenchSource 42.7%—Not comparable
AA Tau3 BankingSource 26.8%—Not comparable
terminalBenchHardSource 50.8%—Not comparable
aaTerminalBench21Source 77.9%—Not comparable
Kimi Claw 24/7Source —46.9%Not comparable
MCP Mark VerifiedSource —81.1%Not comparable
Coding
BenchmarkGLM-5.2Kimi K2.7 CodeResult
SWE-bench ProSource 62.1%—Not comparable
NL2RepoSource 48.9%—Not comparable
Terminal-Bench 2.0Source 81.0%—Not comparable
ProgramBenchSource 63.7%53.6%GLM-5.2 leads
cursorBench32Source 55.0%49.7%GLM-5.2 leads
AA Coding IndexSource 68.8%60.8%GLM-5.2 leads
AA-SciCodeSource 50.5%47.5%GLM-5.2 leads
Kimi Code Bench v2Source —62.0%Not comparable
MLS-Bench LiteSource —35.1%Not comparable
Reasoning
BenchmarkGLM-5.2Kimi K2.7 CodeResult
CritPtSource 20.9%10.0%GLM-5.2 leads
AA-LCRSource 71.3%66.3%GLM-5.2 leads
Knowledge
BenchmarkGLM-5.2Kimi K2.7 CodeResult
GPQASource 91.2%—Not comparable
GPQA-DSource 91.2%—Not comparable
HLESource 54.7%—Not comparable
HLE w/o toolsSource 40.5%—Not comparable
Artificial Analysis Intelligence IndexSource 51.1%42.0%GLM-5.2 leads
AA-GPQA DiamondSource 89.5%89.6%Kimi K2.7 Code leads
AA-HLESource 40.1%32.8%GLM-5.2 leads
AA-Omniscience IndexSource 4.0%-10.7%GLM-5.2 leads
AA-Omniscience AccuracySource 25.1%38.6%Kimi K2.7 Code leads
AA-Omniscience Hallucination RateSource 28.1%80.3%GLM-5.2 leads
AA Openness IndexSource 44.4%—Not comparable
Math
BenchmarkGLM-5.2Kimi K2.7 CodeResult
AIME26Source 99.2%—Not comparable
HMMT Nov 2025Source 94.4%—Not comparable
HMMT Feb 2026Source 92.5%—Not comparable
MMAnswerBenchSource 91.0%—Not comparable
Multimodal
BenchmarkGLM-5.2Kimi K2.7 CodeResult
Design Arena WebsiteSource 13401302GLM-5.2 leads
Inst. Following
BenchmarkGLM-5.2Kimi K2.7 CodeResult
AA-IFBenchSource 73.3%63.1%GLM-5.2 leads
Frequently Asked Questions (3)

Can I compare GLM-5.2 and Kimi K2.7 Code on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for GLM-5.2 and Kimi K2.7 Code today?

GLM-5.2: $1.40 input / $4.40 output per 1M tokens Kimi K2.7 Code: $0.95 input / $4.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

GLM-5.2
API / mo$4,350
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.7 Code
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Model the full break-even

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