Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

MoonshotAI: Kimi K2.5 vs OpenAI: o1 (batch) benchmark

Name: MoonshotAI: Kimi K2.5 vs OpenAI: o1 (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares MoonshotAI: Kimi K2.5 (Moonshot) and OpenAI: o1 (batch) (OpenAI) using the latest snapshots we have as of Aug 16, 2026. MoonshotAI: Kimi K2.5 wins on output price at $2.85/1M. 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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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

OpenAI

OpenAI: o1 (batch)

Auto-discovered from OpenRouter (openai/o1:batch). Preview until a second source matches.

$30/1M 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.

MoonshotAI: Kimi K2.5 (10)vsOpenAI: o1 (batch) (0)

MoonshotAI: Kimi K2.5: 10W (100%)Overall: MoonshotAI: Kimi K2.5OpenAI: o1 (batch): 0W (0%)

← MoonshotAI: Kimi K2.5OpenAI: o1 (batch) →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,515vs—

Coding Elo

1,520vs—

SWE-bench

71.3%vs—

LiveBench

67.2%vs—

GPQA Diamond

87.6%vs—

MoonshotAI: Kimi K2.5: 5WOpenAI: o1 (batch): 0W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

72 tok/svs—

Time to first token

270 msvs—

MoonshotAI: Kimi K2.5: 2WOpenAI: o1 (batch): 0W

MoonshotAI: Kimi K2.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.85/1Mvs$30/1M

Input price

$0.57/1Mvs$7.5/1M

Context window

262kvs200k

MoonshotAI: Kimi K2.5: 3WOpenAI: o1 (batch): 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 K2.5 6/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

MoonshotAI: Kimi K2.5

$27.15/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,515

EloHigh is better

—

Code Elo

High is better

1,520

Code EloHigh is better

—

LiveBench

High is better

67.2%

LiveBenchHigh is better

—

SWE-bench

High is better

71.3%

SWE-benchHigh is better

—

GPQA

High is better

87.6%

GPQAHigh is better

—

TTFT

Low is better

270 ms

TTFTLow is better

—

Speed

High is better

72 tok/s

SpeedHigh is better

—

In $

Low is better

+1216%$0.57/1M

In $Low is better

$7.5/1M

Out $

Low is better

+953%$2.85/1M

Out $Low is better

$30/1M

Context

High is better

+31%262k

ContextHigh is better

200k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 91% 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)

MoonshotAI: Kimi K2.5$62.70 / mo

In: $19.95Out: $42.75

OpenAI: o1 (batch)$712.50 / mo

In: $262.50Out: $450.00

Estimated Cost Delta

MoonshotAI: Kimi K2.5 is estimated to save $649.80/month ($7,798/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
MoonshotAI: Kimi K2.5:Pick MoonshotAI: Kimi K2.5 when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMoonshotAI: Kimi K2.5

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGMoonshotAI: Kimi K2.5

Larger window (262k).

Screenshots / visionMoonshotAI: Kimi K2.5

MoonshotAI: Kimi K2.5 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	MoonshotAI: Kimi K2.5	Lower output list price ($2.85/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	MoonshotAI: Kimi K2.5	Larger window (262k).
Screenshots / vision	MoonshotAI: Kimi K2.5	MoonshotAI: Kimi K2.5 is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

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LIVE

Moonshot

MoonshotAI: Kimi K2.5

Elo 1,515

LiveBench67.2%

SWE-bench71.3%

Speed72 tok/s

Output cost$2.85/1M

OpenAI

OpenAI: o1 (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$30/1M

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2.5 or OpenAI: o1 (batch)?: 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, MoonshotAI: Kimi K2.5 or OpenAI: o1 (batch)?: 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?: MoonshotAI: Kimi K2.5 output tokens are $2.85/1M versus $30/1M. Input prices and retry rates still move the real bill.
Which is faster, MoonshotAI: Kimi K2.5 or OpenAI: o1 (batch)?: We do not have TTFT for both models.
Which has the larger context window?: MoonshotAI: Kimi K2.5 accepts 262k tokens versus 200k.
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. MoonshotAI: Kimi K2.5 and OpenAI: o1 (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All MoonshotAI: Kimi K2.5 matchups →|All OpenAI: o1 (batch) matchups →

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

MoonshotAI: Kimi K2.5 vs OpenAI: o1 (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

MoonshotAI: Kimi K2.5 (10)vsOpenAI: o1 (batch) (0)

MoonshotAI: Kimi K2.5: 10W (100%)Overall: MoonshotAI: Kimi K2.5OpenAI: o1 (batch): 0W (0%)

← MoonshotAI: Kimi K2.5OpenAI: o1 (batch) →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,515vs—

Coding Elo

1,520vs—

SWE-bench

71.3%vs—

LiveBench

67.2%vs—

GPQA Diamond

87.6%vs—

MoonshotAI: Kimi K2.5: 5WOpenAI: o1 (batch): 0W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

72 tok/svs—

Time to first token

270 msvs—

MoonshotAI: Kimi K2.5: 2WOpenAI: o1 (batch): 0W

MoonshotAI: Kimi K2.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.85/1Mvs$30/1M

Input price

$0.57/1Mvs$7.5/1M

Context window

262kvs200k

MoonshotAI: Kimi K2.5: 3WOpenAI: o1 (batch): 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMoonshotAI: Kimi K2.5

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGMoonshotAI: Kimi K2.5

Larger window (262k).

Screenshots / visionMoonshotAI: Kimi K2.5

MoonshotAI: Kimi K2.5 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	MoonshotAI: Kimi K2.5	Lower output list price ($2.85/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	MoonshotAI: Kimi K2.5	Larger window (262k).
Screenshots / vision	MoonshotAI: Kimi K2.5	MoonshotAI: Kimi K2.5 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2.5 or OpenAI: o1 (batch)?

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, MoonshotAI: Kimi K2.5 or OpenAI: o1 (batch)?

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?

MoonshotAI: Kimi K2.5 output tokens are $2.85/1M versus $30/1M. Input prices and retry rates still move the real bill.

Which is faster, MoonshotAI: Kimi K2.5 or OpenAI: o1 (batch)?

We do not have TTFT for both models.

Which has the larger context window?

MoonshotAI: Kimi K2.5 accepts 262k tokens versus 200k.

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. MoonshotAI: Kimi K2.5 and OpenAI: o1 (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.