Intelligence
57.2
57
General reasoning and benchmark headroom.
SituationalGoogle: Gemini 3.1 Pro Preview is a mid-range multimodal generalist from google with a heavy runtime profile, large context posture, and the clearest fit around long-context research / agent workflows.
Benchmark blend
Dev workflow signal
Large
Mid-range tier
Google: Gemini 3.1 Pro Preview currently reads as a mid-range 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.
SituationalTTFT 20.75s
LimitedHow much prompt and task state can stay in view.
Above average$12.00 output / 1M
CompetitiveEditorial Profile
Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation of the Gemini 3 series, it combines high-precision reasoning across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling, see our docs here: https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning. The 3.1 update introduces measurable gains in SWE benchmarks and real-world coding environments, along with stronger autonomous task execution in structured domains such as finance and spreadsheet-based workflows. Designed for advanced development and agentic systems, Gemini 3.1 Pro Preview improves long-horizon stability and tool orchestration while increasing token efficiency. It introduces a new medium thinking level to better balance cost, speed, and performance. The model excels in agentic coding, structured planning, multimodal analysis, and workflow automation, making it well-suited for autonomous agents, financial modeling, spreadsheet automation, and high-context enterprise tasks.
google multimodal profile
Long-context research / Agent workflows with large context and heavy runtime.
Balanced spend profile. Easier to justify in mixed production and exploration workloads.
Large context headroom supports repo-wide prompts and long research sessions.
Vision-capable routing opens up multimodal review and extraction workflows.
Costs look manageable, but still deserve attention in always-on agents or batch jobs.
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.
Software implementation, debugging quality, and coding benchmark signal.
Long-horizon execution quality and interactive benchmark evidence.
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 sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.
Metadata
Verification details remain available, but the page no longer forces them ahead of the editorial read.