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

MoonshotAI: Kimi K2 0711 vs OpenAI: o1-pro (batch) benchmark

Name: MoonshotAI: Kimi K2 0711 vs OpenAI: o1-pro (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares MoonshotAI: Kimi K2 0711 (Moonshot) and OpenAI: o1-pro (batch) (OpenAI) using the latest snapshots we have as of Aug 17, 2026. MoonshotAI: Kimi K2 0711 wins on output price at $2.3/1M. OpenAI: o1-pro (batch) has the larger context window (200k 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 0711

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

Elo 1,465$2.3/1M out

OpenAI

OpenAI: o1-pro (batch)

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

$300/1M 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 0711 (9)vsOpenAI: o1-pro (batch) (1)

MoonshotAI: Kimi K2 0711: 9W (90%)Overall: MoonshotAI: Kimi K2 0711OpenAI: o1-pro (batch): 1W (10%)

← MoonshotAI: Kimi K2 0711OpenAI: o1-pro (batch) →

MoonshotAI: Kimi K2 0711 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,465vs—

Coding Elo

1,470vs—

SWE-bench

65.8%vs—

LiveBench

62.8%vs—

GPQA Diamond

76.5%vs—

MoonshotAI: Kimi K2 0711: 5WOpenAI: o1-pro (batch): 0W

MoonshotAI: Kimi K2 0711 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

85 tok/svs—

Time to first token

240 msvs—

MoonshotAI: Kimi K2 0711: 2WOpenAI: o1-pro (batch): 0W

MoonshotAI: Kimi K2 0711 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.3/1Mvs$300/1M

Input price

$0.57/1Mvs$75/1M

Context window

131kvs200k

MoonshotAI: Kimi K2 0711: 2WOpenAI: o1-pro (batch): 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 0711 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

MoonshotAI: Kimi K2 0711

$297.70/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,465

EloHigh is better

—

Code Elo

High is better

1,470

Code EloHigh is better

—

LiveBench

High is better

62.8%

LiveBenchHigh is better

—

SWE-bench

High is better

65.8%

SWE-benchHigh is better

—

GPQA

High is better

76.5%

GPQAHigh is better

—

TTFT

Low is better

240 ms

TTFTLow is better

—

Speed

High is better

85 tok/s

SpeedHigh is better

—

In $

Low is better

+13058%$0.57/1M

In $Low is better

$75/1M

Out $

Low is better

+12943%$2.3/1M

Out $Low is better

$300/1M

Context

High is better

131k

ContextHigh is better

200k+53%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 99% with MoonshotAI: Kimi K2 0711

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 0711$54.45 / mo

In: $19.95Out: $34.50

OpenAI: o1-pro (batch)$7,125.00 / mo

In: $2625.00Out: $4500.00

Estimated Cost Delta

MoonshotAI: Kimi K2 0711 is estimated to save $7,070.55/month ($84,847/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
MoonshotAI: Kimi K2 0711:Pick MoonshotAI: Kimi K2 0711 when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMoonshotAI: Kimi K2 0711

Lower output list price ($2.3/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: o1-pro (batch)

Larger window (200k).

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	MoonshotAI: Kimi K2 0711	Lower output list price ($2.3/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: o1-pro (batch)	Larger window (200k).
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

Moonshot

MoonshotAI: Kimi K2 0711

Elo 1,465

LiveBench62.8%

SWE-bench65.8%

Speed85 tok/s

Output cost$2.3/1M

OpenAI

OpenAI: o1-pro (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$300/1M

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2 0711 or OpenAI: o1-pro (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 0711 or OpenAI: o1-pro (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 0711 output tokens are $2.3/1M versus $300/1M. Input prices and retry rates still move the real bill.
Which is faster, MoonshotAI: Kimi K2 0711 or OpenAI: o1-pro (batch)?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: o1-pro (batch) accepts 200k 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. MoonshotAI: Kimi K2 0711 and OpenAI: o1-pro (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 0711 matchups →|All OpenAI: o1-pro (batch) matchups →

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

MoonshotAI: Kimi K2 0711 vs OpenAI: o1-pro (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

MoonshotAI: Kimi K2 0711 (9)vsOpenAI: o1-pro (batch) (1)

MoonshotAI: Kimi K2 0711: 9W (90%)Overall: MoonshotAI: Kimi K2 0711OpenAI: o1-pro (batch): 1W (10%)

← MoonshotAI: Kimi K2 0711OpenAI: o1-pro (batch) →

MoonshotAI: Kimi K2 0711 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,465vs—

Coding Elo

1,470vs—

SWE-bench

65.8%vs—

LiveBench

62.8%vs—

GPQA Diamond

76.5%vs—

MoonshotAI: Kimi K2 0711: 5WOpenAI: o1-pro (batch): 0W

MoonshotAI: Kimi K2 0711 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

85 tok/svs—

Time to first token

240 msvs—

MoonshotAI: Kimi K2 0711: 2WOpenAI: o1-pro (batch): 0W

MoonshotAI: Kimi K2 0711 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.3/1Mvs$300/1M

Input price

$0.57/1Mvs$75/1M

Context window

131kvs200k

MoonshotAI: Kimi K2 0711: 2WOpenAI: o1-pro (batch): 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMoonshotAI: Kimi K2 0711

Lower output list price ($2.3/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: o1-pro (batch)

Larger window (200k).

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	MoonshotAI: Kimi K2 0711	Lower output list price ($2.3/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: o1-pro (batch)	Larger window (200k).
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, MoonshotAI: Kimi K2 0711 or OpenAI: o1-pro (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 0711 or OpenAI: o1-pro (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 0711 output tokens are $2.3/1M versus $300/1M. Input prices and retry rates still move the real bill.

Which is faster, MoonshotAI: Kimi K2 0711 or OpenAI: o1-pro (batch)?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: o1-pro (batch) accepts 200k 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. MoonshotAI: Kimi K2 0711 and OpenAI: o1-pro (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.