Model profile
OpenAI

OpenAI: o1-pro

OpenAI: o1-pro is a premium-priced multimodal generalist from OpenAI with partial runtime data, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalN/A latencyLarge contextPremium pricing
Intelligence
25.8

Benchmark blend

Coding
N/A

Dev workflow signal

Context
200K Tokens

Large

Input Price
$150.00

Premium tier

Decision snapshot
39

OpenAI: o1-pro currently reads as a premium multimodal option with large context and a partially published runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Multimodal
Latency tier
N/A
Price tier
Premium
Source coverage
OpenRouterArtificial AnalysisVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
25.8
26

General reasoning and benchmark headroom.

Limited
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
200K Tokens
88

How much prompt and task state can stay in view.

Above average
Price
$150.00
18

$600.00 output / 1M

Premium

Editorial Profile

OpenAI: o1-pro in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score N/AMath score N/AVision enabled

The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...

Identity

OpenAI multimodal profile

Positioning

Long-context research / Multimodal with large context and partially published runtime.

Cost posture

Premium spend profile. Best when the upside justifies tighter budget control.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Pricing sits in premium territory, so bulk usage needs tighter cost controls.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
25.8

Extra benchmark cuts are not available for this category yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
200K Tokens
Vision
Enabled
Modalities
file, image, text
Tokenizer
GPT
Max Completion
100000
Moderation
Yes
Supported Parameters
include_reasoningmax_tokensreasoningresponse_formatseedstructured_outputs
Input Modalities
fileimagetext
Output Modalities
text
Price architecture
Input
per 1M input tokens
$150.00
Output
per 1M output tokens
$600.00
Blended
AA 3:1 mix
$262.50

This model trades into premium territory. It makes sense when capability upside matters more than raw volume efficiency.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.