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

OpenAI: GPT-5.4 Mini (batch) vs MoonshotAI: Kimi K2 0711 benchmark

Name: OpenAI: GPT-5.4 Mini (batch) vs MoonshotAI: Kimi K2 0711 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares OpenAI: GPT-5.4 Mini (batch) (OpenAI) and MoonshotAI: Kimi K2 0711 (Moonshot) using the latest snapshots we have as of Aug 17, 2026. OpenAI: GPT-5.4 Mini (batch) wins on output price at $2.25/1M. OpenAI: GPT-5.4 Mini (batch) has the larger context window (400k 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

OpenAI: GPT-5.4 Mini (batch)

Auto-discovered from OpenRouter (openai/gpt-5.4-mini:batch). Preview until a second source matches.

$2.25/1M out

Moonshot

MoonshotAI: Kimi K2 0711

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

K2 BaseElo 1,465$2.3/1M 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.

OpenAI: GPT-5.4 Mini (batch) (3)vsMoonshotAI: Kimi K2 0711 (7)

OpenAI: GPT-5.4 Mini (batch): 3W (30%)Overall: MoonshotAI: Kimi K2 0711MoonshotAI: Kimi K2 0711: 7W (70%)

← OpenAI: GPT-5.4 Mini (batch)MoonshotAI: Kimi K2 0711 →

MoonshotAI: Kimi K2 0711 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,465

Coding Elo

—vs1,470

SWE-bench

—vs65.8%

LiveBench

—vs62.8%

GPQA Diamond

—vs76.5%

OpenAI: GPT-5.4 Mini (batch): 0WMoonshotAI: Kimi K2 0711: 5W

MoonshotAI: Kimi K2 0711 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs85 tok/s

Time to first token

—vs240 ms

OpenAI: GPT-5.4 Mini (batch): 0WMoonshotAI: Kimi K2 0711: 2W

OpenAI: GPT-5.4 Mini (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.25/1Mvs$2.3/1M

Input price

$0.375/1Mvs$0.57/1M

Context window

400kvs131k

OpenAI: GPT-5.4 Mini (batch): 3WMoonshotAI: Kimi K2 0711: 0W

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 0711 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

OpenAI: GPT-5.4 Mini (batch)

$0.05/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,465

Code Elo

High is better

—

Code EloHigh is better

1,470

LiveBench

High is better

—

LiveBenchHigh is better

62.8%

SWE-bench

High is better

—

SWE-benchHigh is better

65.8%

GPQA

High is better

—

GPQAHigh is better

76.5%

TTFT

Low is better

—

TTFTLow is better

240 ms

Speed

High is better

—

SpeedHigh is better

85 tok/s

In $

Low is better

+52%$0.38 / 1M

In $Low is better

$0.57 / 1M

Out $

Low is better

+2%$2.25 / 1M

Out $Low is better

$2.30 / 1M

Context

High is better

+205%400k

ContextHigh is better

131k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 14% with OpenAI: GPT-5.4 Mini (batch)

Monthly Volume50M tokens/mo

Quick Presets:

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

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

OpenAI: GPT-5.4 Mini (batch)$46.88 / mo

In: $13.13Out: $33.75

MoonshotAI: Kimi K2 0711$54.45 / mo

In: $19.95Out: $34.5

Estimated Cost Delta

OpenAI: GPT-5.4 Mini (batch) is estimated to save $7.58/month ($91/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI: GPT-5.4 Mini (batch):Pick OpenAI: GPT-5.4 Mini (batch) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI: GPT-5.4 Mini (batch)

Lower output list price ($2.25/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.4 Mini (batch)

Larger window (400k).

Screenshots / visionMoonshotAI: Kimi K2 0711

MoonshotAI: Kimi K2 0711 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	OpenAI: GPT-5.4 Mini (batch)	Lower output list price ($2.25/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.4 Mini (batch)	Larger window (400k).
Screenshots / vision	MoonshotAI: Kimi K2 0711	MoonshotAI: Kimi K2 0711 is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

OpenAI

OpenAI: GPT-5.4 Mini (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$2.25/1M

Moonshot

MoonshotAI: Kimi K2 0711

Elo 1,465

LiveBench62.8%

SWE-bench65.8%

Speed85 tok/s

Output cost$2.3/1M

Frequently Asked Questions

Which is better overall, OpenAI: GPT-5.4 Mini (batch) or MoonshotAI: Kimi K2 0711?: 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, OpenAI: GPT-5.4 Mini (batch) or MoonshotAI: Kimi K2 0711?: 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?: OpenAI: GPT-5.4 Mini (batch) output tokens are $2.25/1M versus $2.3/1M. Input prices and retry rates still move the real bill.
Which is faster, OpenAI: GPT-5.4 Mini (batch) or MoonshotAI: Kimi K2 0711?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: GPT-5.4 Mini (batch) accepts 400k tokens versus 131k.
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. OpenAI: GPT-5.4 Mini (batch) and MoonshotAI: Kimi K2 0711 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All OpenAI: GPT-5.4 Mini (batch) matchups →|All MoonshotAI: Kimi K2 0711 matchups →

MoonshotAI: Kimi K2 0711 vs Kimi Chat 1.5 (previous kimi)MoonshotAI: Kimi K2 0711 vs MoonshotAI: Kimi K2.5 (next kimi)GPT-5 vs MoonshotAI: Kimi K2 0711 Kimi K3 vs MoonshotAI: Kimi K2 0711 GPT-4.5 Orion vs MoonshotAI: Kimi K2 0711 GPT-5.6 Sol vs MoonshotAI: Kimi K2 0711

OpenAI: GPT-5.4 Mini (batch) vs MoonshotAI: Kimi K2 0711 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

OpenAI: GPT-5.4 Mini (batch) (3)vsMoonshotAI: Kimi K2 0711 (7)

OpenAI: GPT-5.4 Mini (batch): 3W (30%)Overall: MoonshotAI: Kimi K2 0711MoonshotAI: Kimi K2 0711: 7W (70%)

← OpenAI: GPT-5.4 Mini (batch)MoonshotAI: Kimi K2 0711 →

MoonshotAI: Kimi K2 0711 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,465

Coding Elo

—vs1,470

SWE-bench

—vs65.8%

LiveBench

—vs62.8%

GPQA Diamond

—vs76.5%

OpenAI: GPT-5.4 Mini (batch): 0WMoonshotAI: Kimi K2 0711: 5W

MoonshotAI: Kimi K2 0711 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs85 tok/s

Time to first token

—vs240 ms

OpenAI: GPT-5.4 Mini (batch): 0WMoonshotAI: Kimi K2 0711: 2W

OpenAI: GPT-5.4 Mini (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.25/1Mvs$2.3/1M

Input price

$0.375/1Mvs$0.57/1M

Context window

400kvs131k

OpenAI: GPT-5.4 Mini (batch): 3WMoonshotAI: Kimi K2 0711: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI: GPT-5.4 Mini (batch)

Lower output list price ($2.25/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.4 Mini (batch)

Larger window (400k).

Screenshots / visionMoonshotAI: Kimi K2 0711

MoonshotAI: Kimi K2 0711 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	OpenAI: GPT-5.4 Mini (batch)	Lower output list price ($2.25/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.4 Mini (batch)	Larger window (400k).
Screenshots / vision	MoonshotAI: Kimi K2 0711	MoonshotAI: Kimi K2 0711 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, OpenAI: GPT-5.4 Mini (batch) or MoonshotAI: Kimi K2 0711?

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, OpenAI: GPT-5.4 Mini (batch) or MoonshotAI: Kimi K2 0711?

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?

OpenAI: GPT-5.4 Mini (batch) output tokens are $2.25/1M versus $2.3/1M. Input prices and retry rates still move the real bill.

Which is faster, OpenAI: GPT-5.4 Mini (batch) or MoonshotAI: Kimi K2 0711?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: GPT-5.4 Mini (batch) accepts 400k tokens versus 131k.

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. OpenAI: GPT-5.4 Mini (batch) and MoonshotAI: Kimi K2 0711 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.