Gemini 3.1 Pro
Top-tier reasoning, knowledge and vision with a 1M-token multimodal context.
- Context window
- 1.0Mtokens
- Max output
- 66Ktokens
- Input price
- $2/ 1M tokens
- Output price
- $12/ 1M tokens
- Cached input
- $0.20/ 1M tokens
- Modalities
- Text, Image, Audio, Video, Pdf
- Knowledge cutoff
- Jan 2025
- Released
- Feb 2026
- Approx. speed
- —
What this model is
Gemini 3.1 Pro is Google DeepMind's flagship, benchmarking at or near the very top on knowledge, math, science and multimodal understanding, with an enormous 1M-token context window. It is a superb research, analysis and vision model — but in long autonomous coding sessions it is materially less reliable than the Claude/GPT frontier, and can derail, loop, or corrupt a codebase over a few prompts. Excellent for knowledge work and multimodal reasoning; use with supervision for extended agentic coding.
Strengths
- Elite math, science and knowledge benchmarks
- Best-in-class multimodal (image/video/PDF) understanding
- 1M-token context for huge documents and codebases
- Strong single-shot reasoning and planning
Trade-offs
- Less reliable than Claude/GPT on long agentic coding
- Can derail, loop, or corrupt a codebase over multiple prompts
- Higher latency than the Flash tiers
- Output capped at ~64K tokens
Best for
- Deep research and analysis
- Multimodal reasoning over images, video and PDFs
- Long-context document synthesis
- Math and science problem solving
Not ideal for
- Unsupervised long-horizon coding agents
- Latency-sensitive high-volume traffic
Capability profile
Normalized 0–100 scores, comparable across the whole catalog.
- Reasoning
- 90
- Coding
- 78
- Math
- 94
- Writing
- 89
- Knowledge
- 94
- Speed
- 60
- Agentic
- 76
- Vision
- 95
- Multilingual
- 92
- Long Context
- 96
How it scores
Public benchmark results, with independent third-party results where available. Bars normalize percentages to 100 and Elo ratings to a 1500 ceiling.