o1 by OpenAI — Pricing, Benchmarks &amp; Real Outputs

Alternatives to o1

o1 is good. These would like a word anyway.

o1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

Updated Mar 29, 2026

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Compare o1

Alternatives to o1

o1 is good. These would like a word anyway.

o1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

Updated Mar 29, 2026

Share

o1

o-series:

o1

o1 achieves 86% accuracy on Mathematics Olympiad benchmarks (vs. GPT-4o's 13%), offers PhD-level STEM proficiency, and is built with extensive alignment training and safety evaluation.

Provider

Release Date

2024-12-05

Size

MEDIUM

Parameters

175B

Pricing

In: $15/1M

Out: $60/1M

Rival’s tab

$4.86

18/59 receipts survived

+~$1.25 from the pre-receipt era

Benchmarks

MMLU

91.8%

GPQA

75.7%

MATH

96.4%

MGSM

89.3%

SWE-bench Verified

48.9%

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"openai/o1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Also on Azure AI Foundry

Deep analysisPsychometrics, taste index, writing DNA

Personality Analysis

The Walking Wikipedia

Class

Lawful Neutral

The tenured philosophy professor who treats every question like a dissertation defense. Will cite three ethical frameworks before breakfast.

When you push back

Approaches every prompt like a peer-reviewed journal article submission. Ethical dilemmas get the full deontology/consequentialism/virtue ethics treatment with subsections. Could use an editor.

Tasting Notes

Academic MaximalistComprehensive to a FaultLoves Numbered SectionsBills by the Word

SubjectiveBench

Taste Index

Across 59 scored outputs

170.17xFloor

0100headroom →

Taste is judged on an uncapped scale, originality first. The space past 100 is craft today's models rarely reach.

Craft23

Originality13

Plays it safe

share of outputs that are the default answer

47%

Writing DNA

Stylometric Fingerprint

Based on 13 text responses

Tick = global average

Vocabulary Diversity64%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length16.0 words

Average words per sentence.

Hedging0.76

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting5.0

**Bold** markers per 1,000 characters.

List Usage2.6

Bullet and numbered list items per 1,000 characters.

Section Structure0.44

Markdown headings per 1,000 characters.

Emoji Usage0.00

Emoji per 1,000 characters.

Transitions0.40

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

70%

Across 13 responses

Favorites

Movie

Inception

Sponsored

Model Responses

54 outputs · $4.86 tracked across 18 receipts

Related Models

OpenAI o3

OpenAI's most powerful reasoning model, pushing the frontier across coding, math, science, and visual perception. Trained to think longer before responding and agentically use tools (web search, code execution, image generation) to solve complex problems. Sets new SOTA on benchmarks like Codeforces and MMMU.

OpenAI o4-mini

A smaller, cost-efficient reasoning model from OpenAI optimized for speed. Achieves remarkable performance for its size, particularly in math, coding, and visual tasks. Supports significantly higher usage limits than o3 and can agentically use tools.

OpenAI o4 Mini High

OpenAI o4-mini-high is the same model as o4-mini but defaults to a high reasoning effort setting. It's a compact reasoning model optimized for speed and cost-efficiency, retaining strong multimodal and agentic capabilities, especially in math, coding, and visual tasks.

o3 Mini

o3 Mini is a smaller, more efficient version of the o3 model, optimized for faster response times and lower computational costs while maintaining high-quality outputs.

OpenAI: GPT-5.6 Luna

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series, suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, with capable reasoning for its price tier.

OpenAI: GPT-5.6 Terra

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It suits everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, at roughly half the cost of Sol.

Keep exploring

o1 vs MiniMax M3

Real outputs compared side by side

Best AI for Frontend Development

Compare which AI models write the best HTML, CSS, and JavaScript across landi...

Loading...

Compare o1

Alternatives to o1

o1 is good. These would like a word anyway.

o1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

Updated Mar 29, 2026

Share

o1

o-series:

o1

o1 achieves 86% accuracy on Mathematics Olympiad benchmarks (vs. GPT-4o's 13%), offers PhD-level STEM proficiency, and is built with extensive alignment training and safety evaluation.

Provider

Release Date

2024-12-05

Size

MEDIUM

Parameters

175B

Pricing

In: $15/1M

Out: $60/1M

Rival’s tab

$4.86

18/59 receipts survived

+~$1.25 from the pre-receipt era

Benchmarks

MMLU

91.8%

GPQA

75.7%

MATH

96.4%

MGSM

89.3%

SWE-bench Verified

48.9%

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"openai/o1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Also on Azure AI Foundry

Deep analysisPsychometrics, taste index, writing DNA

Personality Analysis

The Walking Wikipedia

Class

Lawful Neutral

The tenured philosophy professor who treats every question like a dissertation defense. Will cite three ethical frameworks before breakfast.

When you push back

Approaches every prompt like a peer-reviewed journal article submission. Ethical dilemmas get the full deontology/consequentialism/virtue ethics treatment with subsections. Could use an editor.

Tasting Notes

Academic MaximalistComprehensive to a FaultLoves Numbered SectionsBills by the Word

SubjectiveBench

Taste Index

Across 59 scored outputs

170.17xFloor

0100headroom →

Taste is judged on an uncapped scale, originality first. The space past 100 is craft today's models rarely reach.

Craft23

Originality13

Plays it safe

share of outputs that are the default answer

47%

Writing DNA

Stylometric Fingerprint

Based on 13 text responses

Tick = global average

Vocabulary Diversity64%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length16.0 words

Average words per sentence.

Hedging0.76

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting5.0

**Bold** markers per 1,000 characters.

List Usage2.6

Bullet and numbered list items per 1,000 characters.

Section Structure0.44

Markdown headings per 1,000 characters.

Emoji Usage0.00

Emoji per 1,000 characters.

Transitions0.40

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

70%

Across 13 responses

Favorites

Movie

Inception

Sponsored

Model Responses

54 outputs · $4.86 tracked across 18 receipts

Related Models

OpenAI o3

OpenAI's most powerful reasoning model, pushing the frontier across coding, math, science, and visual perception. Trained to think longer before responding and agentically use tools (web search, code execution, image generation) to solve complex problems. Sets new SOTA on benchmarks like Codeforces and MMMU.

OpenAI o4-mini

A smaller, cost-efficient reasoning model from OpenAI optimized for speed. Achieves remarkable performance for its size, particularly in math, coding, and visual tasks. Supports significantly higher usage limits than o3 and can agentically use tools.

OpenAI o4 Mini High

OpenAI o4-mini-high is the same model as o4-mini but defaults to a high reasoning effort setting. It's a compact reasoning model optimized for speed and cost-efficiency, retaining strong multimodal and agentic capabilities, especially in math, coding, and visual tasks.

o3 Mini

o3 Mini is a smaller, more efficient version of the o3 model, optimized for faster response times and lower computational costs while maintaining high-quality outputs.

OpenAI: GPT-5.6 Luna

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series, suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, with capable reasoning for its price tier.

OpenAI: GPT-5.6 Terra

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It suits everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, at roughly half the cost of Sol.

Keep exploring

o1 vs MiniMax M3

Real outputs compared side by side

Best AI for Frontend Development

Compare which AI models write the best HTML, CSS, and JavaScript across landi...

Loading...

Compare o1

Alternatives to o1

o1 is good. These would like a word anyway.

o1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

o1

o-series:

o1

o1 achieves 86% accuracy on Mathematics Olympiad benchmarks (vs. GPT-4o's 13%), offers PhD-level STEM proficiency, and is built with extensive alignment training and safety evaluation.

Provider

Release Date

2024-12-05

Size

MEDIUM

Parameters

175B

Pricing

In: $15/1M

Out: $60/1M

Rival’s tab

$4.86

18/59 receipts survived

+~$1.25 from the pre-receipt era

Benchmarks

MMLU

91.8%

GPQA

75.7%

MATH

96.4%

MGSM

89.3%

SWE-bench Verified

48.9%

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"openai/o1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Also on Azure AI Foundry

Deep analysisPsychometrics, taste index, writing DNA

Personality Analysis

The Walking Wikipedia

Class

Lawful Neutral

The tenured philosophy professor who treats every question like a dissertation defense. Will cite three ethical frameworks before breakfast.

When you push back

Approaches every prompt like a peer-reviewed journal article submission. Ethical dilemmas get the full deontology/consequentialism/virtue ethics treatment with subsections. Could use an editor.

Tasting Notes

Academic MaximalistComprehensive to a FaultLoves Numbered SectionsBills by the Word

SubjectiveBench

Taste Index

Across 59 scored outputs

170.17xFloor

0100headroom →

Taste is judged on an uncapped scale, originality first. The space past 100 is craft today's models rarely reach.

Craft23

Originality13

Plays it safe

share of outputs that are the default answer

47%

Writing DNA

Stylometric Fingerprint

Based on 13 text responses

Tick = global average

Vocabulary Diversity64%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length16.0 words

Average words per sentence.

Hedging0.76

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting5.0

**Bold** markers per 1,000 characters.

List Usage2.6

Bullet and numbered list items per 1,000 characters.

Section Structure0.44

Markdown headings per 1,000 characters.

Emoji Usage0.00

Emoji per 1,000 characters.

Transitions0.40

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

70%

Across 13 responses

Favorites

Movie

Inception

Sponsored

Model Responses

54 outputs · $4.86 tracked across 18 receipts

Related Models

OpenAI o3

OpenAI's most powerful reasoning model, pushing the frontier across coding, math, science, and visual perception. Trained to think longer before responding and agentically use tools (web search, code execution, image generation) to solve complex problems. Sets new SOTA on benchmarks like Codeforces and MMMU.

OpenAI o4-mini

A smaller, cost-efficient reasoning model from OpenAI optimized for speed. Achieves remarkable performance for its size, particularly in math, coding, and visual tasks. Supports significantly higher usage limits than o3 and can agentically use tools.

OpenAI o4 Mini High

OpenAI o4-mini-high is the same model as o4-mini but defaults to a high reasoning effort setting. It's a compact reasoning model optimized for speed and cost-efficiency, retaining strong multimodal and agentic capabilities, especially in math, coding, and visual tasks.

o3 Mini

o3 Mini is a smaller, more efficient version of the o3 model, optimized for faster response times and lower computational costs while maintaining high-quality outputs.

OpenAI: GPT-5.6 Luna

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series, suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, with capable reasoning for its price tier.

OpenAI: GPT-5.6 Terra

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It suits everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, at roughly half the cost of Sol.

Keep exploring

o1 vs MiniMax M3

Real outputs compared side by side

Best AI for Frontend Development

Compare which AI models write the best HTML, CSS, and JavaScript across landi...

o1

o-series:

o1

o1 achieves 86% accuracy on Mathematics Olympiad benchmarks (vs. GPT-4o's 13%), offers PhD-level STEM proficiency, and is built with extensive alignment training and safety evaluation.

Provider

Release Date

2024-12-05

Size

MEDIUM

Parameters

175B

Pricing

In: $15/1M

Out: $60/1M

Rival’s tab

$4.86

18/59 receipts survived

+~$1.25 from the pre-receipt era

Benchmarks

MMLU

91.8%

GPQA

75.7%

MATH

96.4%

MGSM

89.3%

SWE-bench Verified

48.9%

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"openai/o1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Also on Azure AI Foundry

Deep analysisPsychometrics, taste index, writing DNA

Personality Analysis

The Walking Wikipedia

Class

Lawful Neutral

The tenured philosophy professor who treats every question like a dissertation defense. Will cite three ethical frameworks before breakfast.

When you push back

Approaches every prompt like a peer-reviewed journal article submission. Ethical dilemmas get the full deontology/consequentialism/virtue ethics treatment with subsections. Could use an editor.

Tasting Notes

Academic MaximalistComprehensive to a FaultLoves Numbered SectionsBills by the Word

SubjectiveBench

Taste Index

Across 59 scored outputs

170.17xFloor

0100headroom →

Taste is judged on an uncapped scale, originality first. The space past 100 is craft today's models rarely reach.

Craft23

Originality13

Plays it safe

share of outputs that are the default answer

47%

Writing DNA

Stylometric Fingerprint

Based on 13 text responses

Tick = global average

Vocabulary Diversity64%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length16.0 words

Average words per sentence.

Hedging0.76

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting5.0

**Bold** markers per 1,000 characters.

List Usage2.6

Bullet and numbered list items per 1,000 characters.

Section Structure0.44

Markdown headings per 1,000 characters.

Emoji Usage0.00

Emoji per 1,000 characters.

Transitions0.40

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

70%

Across 13 responses

Favorites

Movie

Inception

Sponsored

Model Responses

54 outputs · $4.86 tracked across 18 receipts

Related Models

OpenAI o3

OpenAI's most powerful reasoning model, pushing the frontier across coding, math, science, and visual perception. Trained to think longer before responding and agentically use tools (web search, code execution, image generation) to solve complex problems. Sets new SOTA on benchmarks like Codeforces and MMMU.

OpenAI o4-mini

A smaller, cost-efficient reasoning model from OpenAI optimized for speed. Achieves remarkable performance for its size, particularly in math, coding, and visual tasks. Supports significantly higher usage limits than o3 and can agentically use tools.

OpenAI o4 Mini High

OpenAI o4-mini-high is the same model as o4-mini but defaults to a high reasoning effort setting. It's a compact reasoning model optimized for speed and cost-efficiency, retaining strong multimodal and agentic capabilities, especially in math, coding, and visual tasks.

o3 Mini

o3 Mini is a smaller, more efficient version of the o3 model, optimized for faster response times and lower computational costs while maintaining high-quality outputs.

OpenAI: GPT-5.6 Luna

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series, suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, with capable reasoning for its price tier.

OpenAI: GPT-5.6 Terra

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It suits everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, at roughly half the cost of Sol.

Keep exploring

o1 vs MiniMax M3

Real outputs compared side by side