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Model comparison

Gemini 2.5 Pro vs Kimi K2.7 Code

Data verified

Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

56.6/100
Margin
2.6pts
← winning
Moonshot AI
54.03/100
0 category wins0 category wins

Public leaderboard positions: Gemini 2.5 Pro #76 (Supported); Kimi K2.7 Code #92 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemini 2.5 Pro and Kimi K2.7 Code share 16 comparable benchmark results. 0 of 8 categories are comparable. 8 results are unique to Gemini 2.5 Pro; 7 to Kimi K2.7 Code.

Updated July 27, 2026
Shared results
16
Gemini 2.5 Pro only
8
Kimi K2.7 Code only
7
Comparable categories
0 / 8

Benchmark data for Gemini 2.5 Pro and Kimi K2.7 Code is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 16 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.

Gemini 2.5 Pro is priced at $1.25 input / $10.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.7 Code. Gemini 2.5 Pro 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 Gemini 2.5 Pro and Kimi K2.7 Code
CategoryGemini 2.5 ProΔKimi K2.7 Code
CodingGemini 2.5 Pro63.8MarginNo overlapKimi K2.7 CodeNot measured
KnowledgeGemini 2.5 Pro27.4MarginNo overlapKimi K2.7 CodeNot measured
MathGemini 2.5 Pro11.6MarginNo overlapKimi K2.7 CodeNot measured

Operational comparison

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

MetricGemini 2.5 ProKimi K2.7 CodeComparison
Input / output priceUSD per 1M tokensGemini 2.5 Pro$1.25 input / $10 outputKimi K2.7 Code$0.95 input / $4 outputKimi K2.7 Code has the lower combined listed price.
Generation speedtokens per secondGemini 2.5 Pro117 tok/sKimi K2.7 CodeNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemini 2.5 Pro21.19 sKimi K2.7 CodeNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGemini 2.5 Pro1MKimi K2.7 Code256KGemini 2.5 Pro lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemini 2.5 ProKimi K2.7 CodeResult
AA Agentic IndexSource 7.1%29.6%Kimi K2.7 Code leads
τ²-bench resultsSource 54.1%90.1%Kimi K2.7 Code leads
Gert LabsSource 42.01%Not comparable
GDPval-AASource 8.6%34.3%Kimi K2.7 Code leads
GDPval-AASource 6721186Kimi K2.7 Code leads
Kimi Claw 24/7Source 46.9%Not comparable
MCP AtlasSource 76%Not comparable
MCP Mark VerifiedSource 81.1%Not comparable
Coding
BenchmarkGemini 2.5 ProKimi K2.7 CodeResult
SWE-bench VerifiedSource 63.8%Not comparable
Vibe Code BenchSource 0.40%Not comparable
AA Coding IndexSource 33.3%60.8%Kimi K2.7 Code leads
AA-SciCodeSource 42.8%47.5%Kimi K2.7 Code leads
Kimi Code Bench v2Source 62.0%Not comparable
ProgramBenchSource 53.6%Not comparable
MLS-Bench LiteSource 35.1%Not comparable
cursorBench32Source 49.7%Not comparable
Reasoning
BenchmarkGemini 2.5 ProKimi K2.7 CodeResult
AA-LCRSource 66.0%66.3%Kimi K2.7 Code leads
CritPtSource 2.6%10.0%Kimi K2.7 Code leads
Knowledge
BenchmarkGemini 2.5 ProKimi K2.7 CodeResult
GPQASource 83%Not comparable
HLESource 18.8%Not comparable
Artificial Analysis Intelligence IndexSource 25.8%42.0%Kimi K2.7 Code leads
AA-GPQA DiamondSource 84.4%89.6%Kimi K2.7 Code leads
AA-HLESource 21.1%32.8%Kimi K2.7 Code leads
AA-Omniscience IndexSource -14.3%-10.7%Kimi K2.7 Code leads
AA-Omniscience AccuracySource 39.0%38.6%Gemini 2.5 Pro leads
AA-Omniscience Hallucination RateSource 87.4%80.3%Kimi K2.7 Code leads
Math
BenchmarkGemini 2.5 ProKimi K2.7 CodeResult
FrontierMath v2 (Tiers 1-3)Source 14.138%Not comparable
FrontierMath v2 (Tier 4)Source 4.167%Not comparable
Multimodal
BenchmarkGemini 2.5 ProKimi K2.7 CodeResult
AA-MMMU-ProSource 74.9%Not comparable
Design Arena WebsiteSource 11921300Kimi K2.7 Code leads
Inst. Following
BenchmarkGemini 2.5 ProKimi K2.7 CodeResult
AA-IFBenchSource 48.7%63.1%Kimi K2.7 Code leads
Frequently Asked Questions (3)

Can I compare Gemini 2.5 Pro 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 Gemini 2.5 Pro and Kimi K2.7 Code today?

Gemini 2.5 Pro: $1.25 input / $10.00 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.

Gemini 2.5 Pro
API / mo$8,438
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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Last updated: July 27, 2026

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