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

Dots Studio: Dots3-Note Preview (free) vs OpenAI o1-mini benchmark

Name: Dots Studio: Dots3-Note Preview (free) vs OpenAI o1-mini AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Dots Studio: Dots3-Note Preview (free) (dots-studio) and OpenAI o1-mini (OpenAI) using the latest snapshots we have as of Aug 17, 2026. Dots Studio: Dots3-Note Preview (free) wins on output price at $0/1M. Dots Studio: Dots3-Note Preview (free) has the larger context window (512k 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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dots-studio

Dots Studio: Dots3-Note Preview (free)

Auto-discovered from OpenRouter (dots-studio/dots-3-note-preview:free). Preview until a second source matches.

$0/1M out

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

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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.

Dots Studio: Dots3-Note Preview (free) (3)vsOpenAI o1-mini (7)

Dots Studio: Dots3-Note Preview (free): 3W (30%)Overall: OpenAI o1-miniOpenAI o1-mini: 7W (70%)

← Dots Studio: Dots3-Note Preview (free)OpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,445

Coding Elo

—vs1,468

SWE-bench

—vs56.4%

LiveBench

—vs62%

GPQA Diamond

—vs76.8%

Dots Studio: Dots3-Note Preview (free): 0WOpenAI o1-mini: 5W

OpenAI o1-mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs85 tok/s

Time to first token

—vs280 ms

Dots Studio: Dots3-Note Preview (free): 0WOpenAI o1-mini: 2W

Dots Studio: Dots3-Note Preview (free) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0/1Mvs$4.4/1M

Input price

$0/1Mvs$1.1/1M

Context window

512kvs128k

Dots Studio: Dots3-Note Preview (free): 3WOpenAI o1-mini: 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 AdvantageOpenAI o1-mini 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

Dots Studio: Dots3-Note Preview (free)

$4.40/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,445

Code Elo

High is better

—

Code EloHigh is better

1,468

LiveBench

High is better

—

LiveBenchHigh is better

62%

SWE-bench

High is better

—

SWE-benchHigh is better

56.4%

GPQA

High is better

—

GPQAHigh is better

76.8%

TTFT

Low is better

—

TTFTLow is better

280 ms

Speed

High is better

—

SpeedHigh is better

85 tok/s

In $

Low is better

$0.00 / 1M

In $Low is better

$1.10 / 1M

Out $

Low is better

$0.00 / 1M

Out $Low is better

$4.40 / 1M

Context

High is better

+300%512k

ContextHigh is better

128k

Key Selection Recommendations

1
Dots Studio: Dots3-Note Preview (free):Pick Dots Studio: Dots3-Note Preview (free) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDots Studio: Dots3-Note Preview (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDots Studio: Dots3-Note Preview (free)

Larger window (512k).

Screenshots / visionOpenAI o1-mini

OpenAI o1-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	Dots Studio: Dots3-Note Preview (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Dots Studio: Dots3-Note Preview (free)	Larger window (512k).
Screenshots / vision	OpenAI o1-mini	OpenAI o1-mini is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE

dots-studio

Dots Studio: Dots3-Note Preview (free)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0/1M

OpenAI

OpenAI o1-mini

Elo 1,445

LiveBench62%

SWE-bench56.4%

Speed85 tok/s

Output cost$4.4/1M

Frequently Asked Questions

Which is better overall, Dots Studio: Dots3-Note Preview (free) or OpenAI o1-mini?: 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, Dots Studio: Dots3-Note Preview (free) or OpenAI o1-mini?: 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?: Dots Studio: Dots3-Note Preview (free) output tokens are $0/1M versus $4.4/1M. Input prices and retry rates still move the real bill.
Which is faster, Dots Studio: Dots3-Note Preview (free) or OpenAI o1-mini?: We do not have TTFT for both models.
Which has the larger context window?: Dots Studio: Dots3-Note Preview (free) accepts 512k 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. Dots Studio: Dots3-Note Preview (free) and OpenAI o1-mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Dots Studio: Dots3-Note Preview (free) matchups →|All OpenAI o1-mini matchups →

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

Dots Studio: Dots3-Note Preview (free) vs OpenAI o1-mini benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Dots Studio: Dots3-Note Preview (free) (3)vsOpenAI o1-mini (7)

Dots Studio: Dots3-Note Preview (free): 3W (30%)Overall: OpenAI o1-miniOpenAI o1-mini: 7W (70%)

← Dots Studio: Dots3-Note Preview (free)OpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,445

Coding Elo

—vs1,468

SWE-bench

—vs56.4%

LiveBench

—vs62%

GPQA Diamond

—vs76.8%

Dots Studio: Dots3-Note Preview (free): 0WOpenAI o1-mini: 5W

OpenAI o1-mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs85 tok/s

Time to first token

—vs280 ms

Dots Studio: Dots3-Note Preview (free): 0WOpenAI o1-mini: 2W

Dots Studio: Dots3-Note Preview (free) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0/1Mvs$4.4/1M

Input price

$0/1Mvs$1.1/1M

Context window

512kvs128k

Dots Studio: Dots3-Note Preview (free): 3WOpenAI o1-mini: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDots Studio: Dots3-Note Preview (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDots Studio: Dots3-Note Preview (free)

Larger window (512k).

Screenshots / visionOpenAI o1-mini

OpenAI o1-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	Dots Studio: Dots3-Note Preview (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Dots Studio: Dots3-Note Preview (free)	Larger window (512k).
Screenshots / vision	OpenAI o1-mini	OpenAI o1-mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Dots Studio: Dots3-Note Preview (free) or OpenAI o1-mini?

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, Dots Studio: Dots3-Note Preview (free) or OpenAI o1-mini?

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?

Dots Studio: Dots3-Note Preview (free) output tokens are $0/1M versus $4.4/1M. Input prices and retry rates still move the real bill.

Which is faster, Dots Studio: Dots3-Note Preview (free) or OpenAI o1-mini?

We do not have TTFT for both models.

Which has the larger context window?

Dots Studio: Dots3-Note Preview (free) accepts 512k 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. Dots Studio: Dots3-Note Preview (free) and OpenAI o1-mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.