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

OpenAI o1-mini vs OpenAI: o1-pro (batch) benchmark

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

This page compares OpenAI o1-mini (OpenAI) and OpenAI: o1-pro (batch) (OpenAI) using the latest snapshots we have as of Aug 17, 2026. OpenAI o1-mini wins on output price at $4.4/1M. 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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OpenAI

OpenAI o1-mini

OpenAI high-speed, cost-effective reasoning model optimized for STEM, math, and code generation.

Elo 1,445$4.4/1M 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.

OpenAI o1-mini (9)vsOpenAI: o1-pro (batch) (1)

OpenAI o1-mini: 9W (90%)Overall: OpenAI o1-miniOpenAI: o1-pro (batch): 1W (10%)

← OpenAI o1-miniOpenAI: o1-pro (batch) →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,445vs—

Coding Elo

1,468vs—

SWE-bench

56.4%vs—

LiveBench

62%vs—

GPQA Diamond

76.8%vs—

OpenAI o1-mini: 5WOpenAI: o1-pro (batch): 0W

OpenAI o1-mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

85 tok/svs—

Time to first token

280 msvs—

OpenAI o1-mini: 2WOpenAI: o1-pro (batch): 0W

OpenAI o1-mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4.4/1Mvs$300/1M

Input price

$1.1/1Mvs$75/1M

Context window

128kvs200k

OpenAI o1-mini: 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 AdvantageOpenAI o1-mini 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

OpenAI o1-mini

$295.60/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,445

EloHigh is better

—

Code Elo

High is better

1,468

Code EloHigh is better

—

LiveBench

High is better

62%

LiveBenchHigh is better

—

SWE-bench

High is better

56.4%

SWE-benchHigh is better

—

GPQA

High is better

76.8%

GPQAHigh is better

—

TTFT

Low is better

280 ms

TTFTLow is better

—

Speed

High is better

85 tok/s

SpeedHigh is better

—

In $

Low is better

+6718%$1.1/1M

In $Low is better

$75/1M

Out $

Low is better

+6718%$4.4/1M

Out $Low is better

$300/1M

Context

High is better

128k

ContextHigh is better

200k+56%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 99% with OpenAI o1-mini

Monthly Volume50M tokens/mo

Quick Presets:

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

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

OpenAI o1-mini$104.50 / mo

In: $38.50Out: $66.00

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

In: $2625.00Out: $4500.00

Estimated Cost Delta

OpenAI o1-mini is estimated to save $7,020.50/month ($84,246/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI o1-mini:Pick OpenAI o1-mini when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI o1-mini

Lower output list price ($4.4/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: o1-pro (batch)

Larger window (200k).

Screenshots / visionOpenAI: o1-pro (batch)

OpenAI: o1-pro (batch) 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 o1-mini	Lower output list price ($4.4/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: o1-pro (batch)	Larger window (200k).
Screenshots / vision	OpenAI: o1-pro (batch)	OpenAI: o1-pro (batch) is the side marked multimodal in the catalog.

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LIVE

OpenAI

OpenAI o1-mini

Elo 1,445

LiveBench62%

SWE-bench56.4%

Speed85 tok/s

Output cost$4.4/1M

OpenAI

OpenAI: o1-pro (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$300/1M

Frequently Asked Questions

Which is better overall, OpenAI o1-mini 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, OpenAI o1-mini 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?: OpenAI o1-mini output tokens are $4.4/1M versus $300/1M. Input prices and retry rates still move the real bill.
Which is faster, OpenAI o1-mini 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 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. OpenAI o1-mini 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 OpenAI o1-mini matchups →|All OpenAI: o1-pro (batch) matchups →

OpenAI o1-mini vs GPT-4o mini (previous gpt-mini)OpenAI o1-mini vs OpenAI: o3 Mini (next gpt-mini)GPT-4.5 Orion vs OpenAI o1-mini GPT-5.6 Terra vs OpenAI o1-mini GPT-5 vs OpenAI o1-mini GPT-5.6 Sol vs OpenAI o1-mini

OpenAI o1-mini vs OpenAI: o1-pro (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

OpenAI o1-mini (9)vsOpenAI: o1-pro (batch) (1)

OpenAI o1-mini: 9W (90%)Overall: OpenAI o1-miniOpenAI: o1-pro (batch): 1W (10%)

← OpenAI o1-miniOpenAI: o1-pro (batch) →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,445vs—

Coding Elo

1,468vs—

SWE-bench

56.4%vs—

LiveBench

62%vs—

GPQA Diamond

76.8%vs—

OpenAI o1-mini: 5WOpenAI: o1-pro (batch): 0W

OpenAI o1-mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

85 tok/svs—

Time to first token

280 msvs—

OpenAI o1-mini: 2WOpenAI: o1-pro (batch): 0W

OpenAI o1-mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4.4/1Mvs$300/1M

Input price

$1.1/1Mvs$75/1M

Context window

128kvs200k

OpenAI o1-mini: 2WOpenAI: o1-pro (batch): 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI o1-mini

Lower output list price ($4.4/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: o1-pro (batch)

Larger window (200k).

Screenshots / visionOpenAI: o1-pro (batch)

OpenAI: o1-pro (batch) 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 o1-mini	Lower output list price ($4.4/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: o1-pro (batch)	Larger window (200k).
Screenshots / vision	OpenAI: o1-pro (batch)	OpenAI: o1-pro (batch) is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, OpenAI o1-mini 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, OpenAI o1-mini 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?

OpenAI o1-mini output tokens are $4.4/1M versus $300/1M. Input prices and retry rates still move the real bill.

Which is faster, OpenAI o1-mini 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 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. OpenAI o1-mini and OpenAI: o1-pro (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.