Pairwise benchmark snapshot · Aug 16, 2026

GPT-4o mini vs MoonshotAI: Kimi K2.5 benchmark

Name: GPT-4o mini vs MoonshotAI: Kimi K2.5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-4o mini (OpenAI) 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 243 points (1,515 vs 1,272; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, MoonshotAI: Kimi K2.5 resolves 71.3% versus 41.2% (seed-bootstrap (Aug 1, 2026)). GPT-4o mini streams faster (160 tok/s) while GPT-4o mini is the cheaper output token ($0.6/1M). MoonshotAI: Kimi K2.5 has the larger context window (262k 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.

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OpenAI

GPT-4o mini

Legacy small OpenAI model. Useful as a cheap baseline.

Elo 1,272$0.6/1M 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

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4o mini (4)vsMoonshotAI: Kimi K2.5 (6)

GPT-4o mini: 4W (40%)Overall: MoonshotAI: Kimi K2.5MoonshotAI: Kimi K2.5: 6W (60%)

← GPT-4o miniMoonshotAI: Kimi K2.5 →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,272vs1,515

Coding Elo

—vs1,520

SWE-bench

41.2%vs71.3%

LiveBench

48.1%vs67.2%

GPQA Diamond

60.1%vs87.6%

GPT-4o mini: 0WMoonshotAI: Kimi K2.5: 5W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs72 tok/s

Time to first token

130 msvs270 ms

GPT-4o mini: 2WMoonshotAI: Kimi K2.5: 0W

GPT-4o mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$2.85/1M

Input price

$0.15/1Mvs$0.57/1M

Context window

128kvs262k

GPT-4o mini: 2WMoonshotAI: Kimi K2.5: 1W

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

243 pts advantage

Throughput Speed

GPT-4o mini

88 tok/s faster

Price Efficiency

GPT-4o mini

$2.25/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,272

EloHigh is better

1,515+19%

Code Elo

High is better

—

Code EloHigh is better

1,520

LiveBench

High is better

48.1%

LiveBenchHigh is better

67.2%+40%

SWE-bench

High is better

41.2%

SWE-benchHigh is better

71.3%+73%

GPQA

High is better

60.1%

GPQAHigh is better

87.6%+46%

TTFT

Low is better

+108%130 ms

TTFTLow is better

270 ms

Speed

High is better

+122%160 tok/s

SpeedHigh is better

72 tok/s

In $

Low is better

+280%$0.15/1M

In $Low is better

$0.57/1M

Out $

Low is better

+375%$0.6/1M

Out $Low is better

$2.85/1M

Context

High is better

128k

ContextHigh is better

262k+105%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 77% with GPT-4o mini

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

GPT-4o mini$14.25 / mo

In: $5.25Out: $9.00

MoonshotAI: Kimi K2.5$62.70 / mo

In: $19.95Out: $42.75

Estimated Cost Delta

GPT-4o mini is estimated to save $48.45/month ($581/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
GPT-4o mini:Pick GPT-4o mini when you are optimizing output cost.
3
GPT-4o mini:Pick GPT-4o mini when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsMoonshotAI: Kimi K2.5

Higher SWE-bench (71.3%).

High-volume chatGPT-4o mini

Lower output list price ($0.6/1M).

Voice / low-latency UIGPT-4o mini

Lower TTFT (130 ms).

Long-document RAGMoonshotAI: Kimi K2.5

Larger window (262k).

Screenshots / visionMoonshotAI: Kimi K2.5

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

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	MoonshotAI: Kimi K2.5	Higher SWE-bench (71.3%).
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	GPT-4o mini	Lower TTFT (130 ms).
Long-document RAG	MoonshotAI: Kimi K2.5	Larger window (262k).
Screenshots / vision	MoonshotAI: Kimi K2.5	Both accept images. Defaulting to the higher-Elo side (MoonshotAI: Kimi K2.5).

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LIVE

OpenAI

GPT-4o mini

Elo 1,272

LiveBench48.1%

SWE-bench41.2%

Speed160 tok/s

Output cost$0.6/1M

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, GPT-4o mini 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, GPT-4o mini or MoonshotAI: Kimi K2.5?: MoonshotAI: Kimi K2.5 leads SWE-bench at 71.3% vs 41.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: GPT-4o mini output tokens are $0.6/1M versus $2.85/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-4o mini or MoonshotAI: Kimi K2.5?: GPT-4o mini has the lower time-to-first-token (130 ms vs 270 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: MoonshotAI: Kimi K2.5 accepts 262k tokens versus 128k.
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. GPT-4o mini and MoonshotAI: Kimi K2.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All GPT-4o mini matchups →|All MoonshotAI: Kimi K2.5 matchups →

GPT-4o mini vs OpenAI o1-mini (next gpt-mini)MoonshotAI: Kimi K2.5 vs MoonshotAI: Kimi K2 0711 (previous kimi)MoonshotAI: Kimi K2.5 vs Kimi K3 (next kimi)GPT-5 vs MoonshotAI: Kimi K2.5 GPT-4.5 Orion vs MoonshotAI: Kimi K2.5 GPT-5.6 Sol vs MoonshotAI: Kimi K2.5

GPT-4o mini vs MoonshotAI: Kimi K2.5 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4o mini (4)vsMoonshotAI: Kimi K2.5 (6)

GPT-4o mini: 4W (40%)Overall: MoonshotAI: Kimi K2.5MoonshotAI: Kimi K2.5: 6W (60%)

← GPT-4o miniMoonshotAI: Kimi K2.5 →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,272vs1,515

Coding Elo

—vs1,520

SWE-bench

41.2%vs71.3%

LiveBench

48.1%vs67.2%

GPQA Diamond

60.1%vs87.6%

GPT-4o mini: 0WMoonshotAI: Kimi K2.5: 5W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs72 tok/s

Time to first token

130 msvs270 ms

GPT-4o mini: 2WMoonshotAI: Kimi K2.5: 0W

GPT-4o mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$2.85/1M

Input price

$0.15/1Mvs$0.57/1M

Context window

128kvs262k

GPT-4o mini: 2WMoonshotAI: Kimi K2.5: 1W

Recommended Workload Routing

Repo / coding agentsMoonshotAI: Kimi K2.5

Higher SWE-bench (71.3%).

High-volume chatGPT-4o mini

Lower output list price ($0.6/1M).

Voice / low-latency UIGPT-4o mini

Lower TTFT (130 ms).

Long-document RAGMoonshotAI: Kimi K2.5

Larger window (262k).

Screenshots / visionMoonshotAI: Kimi K2.5

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

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	MoonshotAI: Kimi K2.5	Higher SWE-bench (71.3%).
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	GPT-4o mini	Lower TTFT (130 ms).
Long-document RAG	MoonshotAI: Kimi K2.5	Larger window (262k).
Screenshots / vision	MoonshotAI: Kimi K2.5	Both accept images. Defaulting to the higher-Elo side (MoonshotAI: Kimi K2.5).

Frequently Asked Questions

Which is better overall, GPT-4o mini 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, GPT-4o mini or MoonshotAI: Kimi K2.5?

MoonshotAI: Kimi K2.5 leads SWE-bench at 71.3% vs 41.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

GPT-4o mini output tokens are $0.6/1M versus $2.85/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-4o mini or MoonshotAI: Kimi K2.5?

GPT-4o mini has the lower time-to-first-token (130 ms vs 270 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

MoonshotAI: Kimi K2.5 accepts 262k tokens versus 128k.

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. GPT-4o mini and MoonshotAI: Kimi K2.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.