Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

GPT-4o mini vs MoonshotAI: Kimi K2.7 Code benchmark

Name: GPT-4o mini vs MoonshotAI: Kimi K2.7 Code AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-4o mini (OpenAI) and MoonshotAI: Kimi K2.7 Code (Moonshot) using the latest snapshots we have as of Aug 17, 2026. GPT-4o mini wins on output price at $0.6/1M. MoonshotAI: Kimi K2.7 Code 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.

4o MiniElo 1,272$0.6/1M out

Moonshot

MoonshotAI: Kimi K2.7 Code

Auto-discovered from OpenRouter (moonshotai/kimi-k2.7-code). Preview until a second source matches.

$3.5/1M out

Model Lineage & Multi-Tier Derivatives🇺🇸 US Frontier

GPT-4 Series Family (4 models)

Compare vs Base (GPT-4o)

GPT-4o

OpenAI

Flagship Base

Elo

1335

Speed

110 tok/s

Price

$10.00 / 1M

View model →vs this

GPT-4o mini

OpenAI

4o Mini

Elo

1272

Speed

160 tok/s

Price

$0.60 / 1M

-63 Elo-94% cost1.5x speed

Viewing now

GPT-4.5 Orion

OpenAI

Derivative

Elo

1540

Speed

60 tok/s

Price

$150.00 / 1M

+205 Elo+1400% cost0.5x speed

View model →vs this

OpenAI: GPT-4

OpenAI

Derivative

Elo

—

Speed

—

Price

$60.00 / 1M

+500% cost

View model →vs this

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

Model A

Model B

Quick vs:vs Claude Opus 4.5 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 (8)vsMoonshotAI: Kimi K2.7 Code (1)

GPT-4o mini: 8W (89%)Overall: GPT-4o miniMoonshotAI: Kimi K2.7 Code: 1W (11%)

← GPT-4o miniMoonshotAI: Kimi K2.7 Code →

GPT-4o mini (4/5)

Intelligence & Reasoning

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

Preference Elo

1,272vs—

Coding Elo

—vs—

SWE-bench

41.2%vs—

LiveBench

48.1%vs—

GPQA Diamond

60.1%vs—

GPT-4o mini: 4WMoonshotAI: Kimi K2.7 Code: 0W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs—

Time to first token

130 msvs—

GPT-4o mini: 2WMoonshotAI: Kimi K2.7 Code: 0W

GPT-4o mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$3.5/1M

Input price

$0.15/1Mvs$0.71/1M

Context window

128kvs262k

GPT-4o mini: 2WMoonshotAI: Kimi K2.7 Code: 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 AdvantageGPT-4o mini 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

GPT-4o mini

$2.90/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,272

EloHigh is better

—

LiveBench

High is better

48.1%

LiveBenchHigh is better

—

SWE-bench

High is better

41.2%

SWE-benchHigh is better

—

GPQA

High is better

60.1%

GPQAHigh is better

—

TTFT

Low is better

130 ms

TTFTLow is better

—

Speed

High is better

160 tok/s

SpeedHigh is better

—

In $

Low is better

+373%$0.15 / 1M

In $Low is better

$0.71 / 1M

Out $

Low is better

+483%$0.60 / 1M

Out $Low is better

$3.50 / 1M

Context

High is better

128k

ContextHigh is better

262k+105%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 82% 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

MoonshotAI: Kimi K2.7 Code$77.35 / mo

In: $24.85Out: $52.5

Estimated Cost Delta

GPT-4o mini is estimated to save $63.10/month ($757/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
GPT-4o mini:Pick GPT-4o mini when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGPT-4o mini

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGMoonshotAI: Kimi K2.7 Code

Larger window (262k).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	MoonshotAI: Kimi K2.7 Code	Larger window (262k).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE

OpenAI

GPT-4o mini

Elo 1,272

LiveBench48.1%

SWE-bench41.2%

Speed160 tok/s

Output cost$0.6/1M

Moonshot

MoonshotAI: Kimi K2.7 Code

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$3.5/1M

Frequently Asked Questions

Which is better overall, GPT-4o mini or MoonshotAI: Kimi K2.7 Code?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, GPT-4o mini or MoonshotAI: Kimi K2.7 Code?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: GPT-4o mini output tokens are $0.6/1M versus $3.5/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-4o mini or MoonshotAI: Kimi K2.7 Code?: We do not have TTFT for both models.
Which has the larger context window?: MoonshotAI: Kimi K2.7 Code 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 K2.7 Code 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 K2.7 Code matchups →

GPT-4o mini vs OpenAI o1-mini (next gpt-mini)GPT-5 vs GPT-4o mini Kimi K3 vs GPT-4o mini GPT-4.5 Orion vs GPT-4o mini GPT-5.6 Sol vs GPT-4o mini GPT-5.6 Terra vs GPT-4o mini

GPT-4o mini vs MoonshotAI: Kimi K2.7 Code benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4o mini (8)vsMoonshotAI: Kimi K2.7 Code (1)

GPT-4o mini: 8W (89%)Overall: GPT-4o miniMoonshotAI: Kimi K2.7 Code: 1W (11%)

← GPT-4o miniMoonshotAI: Kimi K2.7 Code →

GPT-4o mini (4/5)

Intelligence & Reasoning

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

Preference Elo

1,272vs—

Coding Elo

—vs—

SWE-bench

41.2%vs—

LiveBench

48.1%vs—

GPQA Diamond

60.1%vs—

GPT-4o mini: 4WMoonshotAI: Kimi K2.7 Code: 0W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs—

Time to first token

130 msvs—

GPT-4o mini: 2WMoonshotAI: Kimi K2.7 Code: 0W

GPT-4o mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$3.5/1M

Input price

$0.15/1Mvs$0.71/1M

Context window

128kvs262k

GPT-4o mini: 2WMoonshotAI: Kimi K2.7 Code: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGPT-4o mini

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGMoonshotAI: Kimi K2.7 Code

Larger window (262k).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	MoonshotAI: Kimi K2.7 Code	Larger window (262k).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, GPT-4o mini or MoonshotAI: Kimi K2.7 Code?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, GPT-4o mini or MoonshotAI: Kimi K2.7 Code?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

GPT-4o mini output tokens are $0.6/1M versus $3.5/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-4o mini or MoonshotAI: Kimi K2.7 Code?

We do not have TTFT for both models.

Which has the larger context window?

MoonshotAI: Kimi K2.7 Code 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 K2.7 Code Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.