Intelligence
25.8
26
General reasoning and benchmark headroom.
LimitedOpenAI: o1-pro is a premium multimodal generalist from openai with a heavy runtime profile, large context posture, and the clearest fit around long-context research / multimodal.
Benchmark blend
Dev workflow signal
Large
Premium tier
OpenAI: o1-pro currently reads as a premium multimodal option with large context and a heavy runtime profile.
Decision Strip
Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.
General reasoning and benchmark headroom.
LimitedLatency data is partial.
SituationalHow much prompt and task state can stay in view.
Above average$600.00 output / 1M
PremiumEditorial Profile
Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.
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 consistently better answers.
openai multimodal profile
Long-context research / Multimodal with large context and heavy runtime.
Premium spend profile. Best when the upside justifies tighter budget control.
Large context headroom supports repo-wide prompts and long research sessions.
Vision-capable routing opens up multimodal review and extraction workflows.
Pricing sits in premium territory, so bulk usage needs tighter cost controls.
Latency profile is better for deliberate runs than rapid back-and-forth chat.
Image-grounded review, multimodal extraction, and UI audit workflows.
Long-context summarization, repo analysis, and policy or document review.
Benchmarks
Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.
Broad reasoning, knowledge depth, and flagship benchmark posture.
Extra benchmark cuts are not available for this category yet.
Specs & Pricing
Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.
This model trades into premium territory. It makes sense when capability upside matters more than raw volume efficiency.
Metadata
Verification details remain available, but the page no longer forces them ahead of the editorial read.