CompareLLM
CompareLLM.ai
Live
LeaderboardModelsCompareStacksBest ofGuidesNewsMethod
…
CompareLLM
CompareLLM.ai
Precision Benchmarks

Programmatic, dated AI model benchmarks, head-to-head comparisons, and Stack Engine presets.

Daily ingest · 06:00 UTC

Analytics & Benchmarks

  • AI Model Leaderboard
  • Head-to-Head Compare Hub
  • Models Directory
  • Stack Engine Presets
  • Frontier Models
  • Open Weights Catalog

Guides & Intent Lists

  • Best LLM Lists (2026)
  • Best Coding LLM
  • Best Cheap LLM
  • Fastest Low-Latency LLM
  • Claude vs GPT Benchmark
  • What is Elo?
  • Methodology Guides
  • News & Dispatches

Transparency & API

  • Evaluation Methodology
  • Benchmark Changelog
  • Public JSON API
  • llms.txt Specification
  • Privacy Policy
  • Sign In / Account

© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

  1. Home
  2. Comparisons
  3. Gemini 2.5 Pro vs MoonshotAI: Kimi K2.5

Pairwise benchmark snapshot · Aug 16, 2026

Gemini 2.5 Pro vs MoonshotAI: Kimi K2.5 benchmark

This page compares Gemini 2.5 Pro (Google) and MoonshotAI: Kimi K2.5 (Moonshot) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, MoonshotAI: Kimi K2.5 is ahead by 165 points (1,515 vs 1,350; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, MoonshotAI: Kimi K2.5 resolves 71.3% versus 63.8% (seed-bootstrap (Aug 1, 2026)). Gemini 2.5 Pro streams faster (95 tok/s) while MoonshotAI: Kimi K2.5 is the cheaper output token ($2.85/1M). Gemini 2.5 Pro has the larger context window (1M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

Quick answer

Gemini 2.5 Pro vs MoonshotAI: Kimi K2.5 is a dated snapshot, not a lab score. MoonshotAI: Kimi K2.5 leads preference Elo (1,515 vs 1,350). MoonshotAI: Kimi K2.5 leads SWE-bench coding. MoonshotAI: Kimi K2.5 is the cheaper output token. Elo is crowd preference, not an exam. Pick the column that matches the job.
Share Analysis:
WhatsAppTelegramX / PostLinkedInReddit

Google

Gemini 2.5 Pro

Previous Google long-context flagship.

Elo 1,350$10/1M out

Moonshot

MoonshotAI: Kimi K2.5

Auto-discovered from OpenRouter (moonshotai/kimi-k2.5). Preview until a second source matches.

Elo 1,515$2.8499999999999996/1M out

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

Model A
Model B
Quick vs:vs Claude Opus 4.5vs Claude Opus 4.6vs Claude Sonnet 4.5vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.5 Pro (3)vsMoonshotAI: Kimi K2.5 (7)
Gemini 2.5 Pro: 3W (30%)Overall: MoonshotAI: Kimi K2.5MoonshotAI: Kimi K2.5: 7W (70%)
← Gemini 2.5 ProMoonshotAI: Kimi K2.5 →
MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo
1,350vs1,515
Coding Elo
—vs1,520
SWE-bench
63.8%vs71.3%
LiveBench
57.1%vs67.2%
GPQA Diamond
76.4%vs87.6%
Gemini 2.5 Pro: 0WMoonshotAI: Kimi K2.5: 5W
Gemini 2.5 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed
95 tok/svs72 tok/s
Time to first token
210 msvs270 ms
Gemini 2.5 Pro: 2WMoonshotAI: Kimi K2.5: 0W
MoonshotAI: Kimi K2.5 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price
$10/1Mvs$2.85/1M
Input price
$1.25/1Mvs$0.57/1M
Context window
1Mvs262k
Gemini 2.5 Pro: 1WMoonshotAI: Kimi K2.5: 2W
Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect
Percentile 0–100
Dimensional AdvantageMoonshotAI: Kimi K2.5 4/6
Preference Elo

MoonshotAI: Kimi K2.5

165 pts advantage

Throughput Speed

Gemini 2.5 Pro

23 tok/s faster

Price Efficiency

MoonshotAI: Kimi K2.5

$7.15/1M cheaper

Full Benchmark Score Matrix

—
Elo
High is better
1,350
EloHigh is better
1,515+12%
Code Elo
High is better
—
Code EloHigh is better
1,520
LiveBench
High is better
57.1%
LiveBenchHigh is better
67.2%+18%
SWE-bench
High is better
63.8%
SWE-benchHigh is better
71.3%+12%
GPQA
High is better
76.4%
GPQAHigh is better
87.6%+15%
TTFT
Low is better
+29%210 ms
TTFTLow is better
270 ms
Speed
High is better
+32%95 tok/s
SpeedHigh is better
72 tok/s
In $
Low is better
$1.25/1M
In $Low is better
$0.57/1M+119%
Out $
Low is better
$10/1M
Out $Low is better
$2.85/1M+251%
Context
High is better
+300%1M
ContextHigh is better
262k
Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 68% with MoonshotAI: Kimi K2.5
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Gemini 2.5 Pro$193.75 / mo
In: $43.75Out: $150.00
MoonshotAI: Kimi K2.5$62.70 / mo
In: $19.95Out: $42.75
Estimated Cost Delta

MoonshotAI: Kimi K2.5 is estimated to save $131.05/month ($1,573/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    MoonshotAI: Kimi K2.5:Pick MoonshotAI: Kimi K2.5 when repo-level coding accuracy is the constraint.
  • 2
    Gemini 2.5 Pro:Pick Gemini 2.5 Pro when time-to-first-token matters more than peak Elo.
  • 3
    Gemini 2.5 Pro:Pick Gemini 2.5 Pro for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsMoonshotAI: Kimi K2.5

Higher SWE-bench (71.3%).

High-volume chatMoonshotAI: Kimi K2.5

Lower output list price ($2.85/1M).

Voice / low-latency UIGemini 2.5 Pro

Lower TTFT (210 ms).

Long-document RAGGemini 2.5 Pro

Larger window (1M).

Screenshots / visionMoonshotAI: Kimi K2.5

Both accept images. Defaulting to the higher-Elo side (MoonshotAI: Kimi K2.5).

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsMoonshotAI: Kimi K2.5Higher SWE-bench (71.3%).
High-volume chatMoonshotAI: Kimi K2.5Lower output list price ($2.85/1M).
Voice / low-latency UIGemini 2.5 ProLower TTFT (210 ms).
Long-document RAGGemini 2.5 ProLarger window (1M).
Screenshots / visionMoonshotAI: Kimi K2.5Both accept images. Defaulting to the higher-Elo side (MoonshotAI: Kimi K2.5).

Related Editorial Dispatches & Benchmark Notes

View all news
launchMar 25, 2025

Gemini 2.5 Pro remains the previous Google long-context flagship

2025-03 row. 3.x Pro replaced it. Kept for old “2.5 pro vs gpt-4o” inbound.

Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

Sign in to cast your verified vote, bookmark models, and participate in benchmark discussions.Sign In to Post

No comments posted on this matchup yet. Be the first to share an evaluation note!

Share card

The real PNG is generated at /compare/gemini-2-5-pro-vs-kimi-k2-5/opengraph-image for crawlers.

PNG

CompareLLM Matrix

Verified head-to-head card

LIVE
VS
Google

Gemini 2.5 Pro

Elo 1,350
LiveBench57.1%
SWE-bench63.8%
Speed95 tok/s
Output cost$10/1M
Moonshot

MoonshotAI: Kimi K2.5

Elo 1,515
LiveBench67.2%
SWE-bench71.3%
Speed72 tok/s
Output cost$2.85/1M

Frequently Asked Questions

Which is better overall, Gemini 2.5 Pro or MoonshotAI: Kimi K2.5?
MoonshotAI: Kimi K2.5 has the higher preference Elo in our latest snapshot (1,515). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Gemini 2.5 Pro or MoonshotAI: Kimi K2.5?
MoonshotAI: Kimi K2.5 leads SWE-bench at 71.3% vs 63.8%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?
MoonshotAI: Kimi K2.5 output tokens are $2.85/1M versus $10/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 2.5 Pro or MoonshotAI: Kimi K2.5?
Gemini 2.5 Pro has the lower time-to-first-token (210 ms vs 270 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?
Gemini 2.5 Pro accepts 1M tokens versus 262k.
Can I self-host either model?
Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?
No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?
Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Gemini 2.5 Pro and MoonshotAI: Kimi K2.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • launch · Mar 25, 2025

    Gemini 2.5 Pro remains the previous Google long-context flagship

Similar Head-to-Head Comparisons

All Gemini 2.5 Pro matchups →|All MoonshotAI: Kimi K2.5 matchups →
Gemini 2.5 Pro vs Gemini 1.5 Pro (previous gemini-pro)Gemini 2.5 Pro vs Gemini 3 Pro (next gemini-pro)MoonshotAI: Kimi K2.5 vs MoonshotAI: Kimi K2 0711 (previous kimi)MoonshotAI: Kimi K2.5 vs Kimi K3 (next kimi)Gemini 2.0 Flash Thinking vs MoonshotAI: Kimi K2.5Gemini 3 Flash vs MoonshotAI: Kimi K2.5