Google's reasoning-focused Gemini 3.1 Pro preview for coding and complex analysis, with a 1M-token context and $2/$12 per million pricing.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
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gemini 3.1 pro preview is Google's frontier-tier reasoning model in the 3.1 generation, the one to reach for when a task needs multiple steps of thinking, not just fast pattern matching. It's built for coding, complex analysis, and agentic problem solving where getting the answer right matters more than shaving a few cents off the bill. Developers building coding assistants, research agents, or anything that chains several reasoning steps together are the target audience.
The model carries a 1,048,576 token context window with up to 65,536 tokens of output per call — enough room to hold a full codebase excerpt, a long research thread, or a multi-document brief in one request. Input tokens cost $2.00 per million, output tokens $12.00 per million, and cached input is $0.20 per million. That 6x output-to-input price ratio is worth planning around: verbose responses cost real money here, so prompts that ask for concise, structured output pay off more than they would on a cheaper tier.
Gemini 3.1 Flash Lite Preview costs $0.25 per million input and $1.50 per million output — an 8x discount on both sides — and posts a capability score of 88.6 against Pro Preview's 88.5. On paper those scores are nearly identical, which is a real signal: for tasks that don't need Pro's depth, Flash Lite is worth testing first, and reserving Pro for the harder end of the workload where multi-step reasoning actually shows up is the more defensible default than routing everything to the most expensive tier.
As a preview release, pricing, output limits, and availability aren't locked in, and Google can change them before general availability ships. There's no benchmark suite attached to this listing, so treat capability comparisons as a rough signal, not a ranking — run your own eval against your own task before committing a production workload to it.
Use the recorded facts as a shortlist, then validate the model against representative inputs and production constraints.
Gemini 3.1 Pro Preview is categorized for Audio-text-to-text, Automatic speech recognition, Image-text-to-text, Image-to-text, Text generation, Text-to-text AI models, Video-text-to-text. Its current record accepts text, image, video, audio, pdf and produces text. Confirm file formats, preprocessing, and provider-specific request schemas before implementation.
The directory records 1.0M context and 65.5K maximum output. Listed token prices are $2.00 input and $12.00 output per 1M tokens. Treat missing values as unknown and recheck current commercial terms.
Recorded output speed is — and time to first token is —. Hosting route, region, prompt length, concurrency, and provider load can materially change both measurements.
This page separates sourced model facts from incomplete fields. Benchmark evidence is displayed only when its source is linked and verified. Before choosing Gemini 3.1 Pro Preview, test task quality, tool reliability, safety behavior, data controls, rate limits, and total cost on the exact route you intend to use.
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Google's low-cost Gemini 3 model with a 1,048,576-token context window, vision support, and $0.30/$2.50 per million token pricing for volume workloads.
Google's mid-tier Gemini 3 model: 1,048,576-token context, multimodal input, and $1.50/$7.50 per million token pricing for production agent workloads.
Google's cheapest Gemini 3 model, with a 1,048,576-token context window and $0.25/$1.50 per million token pricing for high-volume, cost-sensitive work.
Google's full Gemini 3 Flash model, with a 1,048,576-token context window and $1.50/$9.00 per million token pricing for production-grade agent work.
Google's fast, rolling-updated Gemini model with a 1M-token context window, reasoning, and tool calling at $1.50/$9.00 per million tokens.
Google's low-cost, high-volume Gemini model at $0.25/$1.50 per million tokens, with a 1M-token context window and reasoning support.