Skip to main content
BenchLM
Advertise

Model comparison

GLM-4.7-Flash vs Kimi K2.5

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
N/A
No comparison
Kimi K2.5
Moonshot AI
59.66/100
0 category wins0 category wins

Public leaderboard positions: GLM-4.7-Flash #106 (Supported); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-4.7-Flash and Kimi K2.5 share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to GLM-4.7-Flash; 63 to Kimi K2.5.

Updated July 21, 2026
Shared results
0
GLM-4.7-Flash only
0
Kimi K2.5 only
63
Comparable categories
0 / 8

Benchmark data for GLM-4.7-Flash and Kimi K2.5 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for GLM-4.7-Flash yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.

Kimi K2.5 is priced at $0.60 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7-Flash. Kimi K2.5 has the larger context window at 256K, compared with 200K for GLM-4.7-Flash.

Operational comparison

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

MetricGLM-4.7-FlashKimi K2.5Comparison
Input / output priceUSD per 1M tokensGLM-4.7-Flash$0 input / $0 outputKimi K2.5$0.6 input / $3 outputGLM-4.7-Flash has the lower combined listed price.
Generation speedtokens per secondGLM-4.7-Flash95 tok/sKimi K2.545 tok/sGLM-4.7-Flash has the higher measured throughput.
First-answer latencyseconds to first tokenGLM-4.7-Flash0.91 sKimi K2.52.38 sGLM-4.7-Flash reaches the first token sooner.
Context windowmaximum listed tokensGLM-4.7-Flash200KKimi K2.5256KKimi K2.5 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-4.7-FlashKimi K2.5Result
Terminal-Bench 2.0Source —50.8%Not comparable
BrowseCompSource —60.6%Not comparable
Claw-EvalSource —52.3%Not comparable
QwenClawBenchSource —54.3%Not comparable
τ³-bench resultsSource —65.7%Not comparable
DeepSearchQASource —77.1%Not comparable
DeepPlanningSource —14.4%Not comparable
ToolathlonSource —27.8%Not comparable
MCP AtlasSource —29.5%Not comparable
MCP-TasksSource —59.1%Not comparable
WideResearchSource —72.7%Not comparable
τ²-bench resultsSource —95.9%Not comparable
APEX-Agents-AASource —11.5%Not comparable
Gert LabsSource —45.88%Not comparable
ResearchClawBenchSource —14.0%Not comparable
JobBenchSource —8.7%Not comparable
AA Agentic IndexSource —21.7%Not comparable
GDPval-AASource —25.4%Not comparable
GDPval-AASource —1009Not comparable
Coding
BenchmarkGLM-4.7-FlashKimi K2.5Result
SWE-bench VerifiedSource —76.8%Not comparable
SWE-bench Verified*Source —70.8%Not comparable
LiveCodeBench v6Source —85.0%Not comparable
SWE-bench ProSource —50.7%Not comparable
SWE MultilingualSource —73%Not comparable
SWE-RebenchSource —58.5%Not comparable
React Native EvalsSource —77.2%Not comparable
SciCodeSource —48.7%Not comparable
AA-SciCodeSource —49.0%Not comparable
AA Coding IndexSource —46.8%Not comparable
Reasoning
BenchmarkGLM-4.7-FlashKimi K2.5Result
LongBench v2Source —61%Not comparable
AA-LCRSource —65.3%Not comparable
CritPtSource —3.1%Not comparable
Knowledge
BenchmarkGLM-4.7-FlashKimi K2.5Result
GPQASource —87.6%Not comparable
GPQA-DSource —87.6%Not comparable
SuperGPQASource —69.2%Not comparable
MMLU-ProSource —87.1%Not comparable
MMLU-Pro (Arcee)Source —87.1%Not comparable
HLESource —30.1%Not comparable
Artificial Analysis Intelligence IndexSource —35.4%Not comparable
AA-GPQA DiamondSource —87.9%Not comparable
AA-HLESource —29.4%Not comparable
AA-Omniscience IndexSource —-8.1%Not comparable
AA-Omniscience AccuracySource —34.3%Not comparable
AA-Omniscience Hallucination RateSource —64.6%Not comparable
Math
BenchmarkGLM-4.7-FlashKimi K2.5Result
AIME 2025Source —96.1%Not comparable
AIME26Source —95.8%Not comparable
AIME25 (Arcee)Source —96.3%Not comparable
HMMT Feb 2025Source —95.4%Not comparable
HMMT Nov 2025Source —91.1%Not comparable
HMMT Feb 2026Source —87.1%Not comparable
MMAnswerBenchSource —81.8%Not comparable
FrontierMath v2 (Tiers 1-3)Source —27.900%Not comparable
FrontierMath v2 (Tier 4)Source —4.200%Not comparable
Multilingual
BenchmarkGLM-4.7-FlashKimi K2.5Result
MMLU-ProXSource —82.3%Not comparable
NOVA-63Source —56.0%Not comparable
Multimodal
BenchmarkGLM-4.7-FlashKimi K2.5Result
MMMU-ProSource —78.5%Not comparable
Video-MMESource —87.4%Not comparable
MMVUSource —80.4%Not comparable
VideoMMMUSource —86.6%Not comparable
AA-MMMU-ProSource —75.4%Not comparable
Design Arena WebsiteSource —1279Not comparable
Inst. Following
BenchmarkGLM-4.7-FlashKimi K2.5Result
IFEvalSource —93.9%Not comparable
AA-IFBenchSource —70.2%Not comparable
Frequently Asked Questions (3)

Can I compare GLM-4.7-Flash and Kimi K2.5 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-4.7-Flash and Kimi K2.5 today?

GLM-4.7-Flash: $0.00 input / $0.00 output per 1M tokens Kimi K2.5: $0.60 input / $3.00 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-4.7-Flash
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.5
API / mo$2,700
Self-host / mo$5,221
Break-even132M/day
Model the full break-even

Related Comparisons

Explore More

Z.AI Compare Pricing Methodology Find Your Best LLM Overall Rankings
Last updated: July 21, 2026

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.