2M token context window — the largest of any frontier model
Leads ARC-AGI-2 reasoning benchmark at 77.1%
Best price-to-performance among premium models at $2/$12 per 1M tokens
Weaknesses
Slower than Flash for everyday lightweight tasks
Claude Sonnet 4.6 is better for writing quality
Real-world use cases
What people actually use Gemini 3.1 Pro for.
Analyzing entire contracts, codebases, or research corpora in a single 2M-token prompt
Due diligence synthesis across large sets of financial documents or legal agreements
Multi-step reasoning across dense technical specifications with Deep Think mode
How Gemini 3.1 Pro compares
The nearest models people weigh against it, and what actually separates them.
vs Gemini 3.5 Flash — Against Gemini 3.5 Flash (Google), Gemini 3.1 Pro costs about 25% more per token, takes 1.9x the context and answers slower. Gemini 3.5 Flash is the one to check first if the price difference matters more than the ceiling.
vs Gemini 3.6 Flash — Against Gemini 3.6 Flash (Google), Gemini 3.1 Pro costs about 68% more per token, takes 1.9x the context and answers slower. Gemini 3.6 Flash is the one to check first if the price difference matters more than the ceiling.
vs GPT-6 Astra — Against GPT-6 Astra (OpenAI), Gemini 3.1 Pro runs about 77% cheaper per token, takes 1.9x the context and answers faster. Take Gemini 3.1 Pro unless you specifically need what GPT-6 Astra does better.
Price History
Gemini 3.1 Pro pricing over time
→0% since May 17
90 data points · tracked daily since May 17, 2026
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Research, deep document analysis, and long-context reasoning at competitive pricing. Start free — no card required.
Google's I/O 2026 headliner — a Flash-tier model that beats Gemini 3.1 Pro on agentic and coding benchmarks while running roughly 4x faster than comparable frontier models.
Verdict
Excellent fast agentic model, superseded by Gemini 3.6 Flash.
Quality score
89%
Pricing
$1.50/1M in
$9.00/1M out
Speed
Fast
4/5 speed
Context
1.0M tokens
Released at Google I/O, May 19, 2026. Batch API half price; context caching $0.15/1M. 65,536-token output limit.
Google's efficiency-focused successor to 3.5 Flash — higher scores on every benchmark Google tested, ~17% fewer output tokens, and cheaper output pricing.
Verdict
Best Gemini for agents — efficiency king with native computer use.
Quality score
90%
Pricing
$0.75/1M in
$3.75/1M out
Speed
Fast
4/5 speed
Context
1.0M tokens
Released July 21, 2026 alongside 3.5 Flash-Lite and the gated 3.5 Flash Cyber. Knowledge cutoff March 2026. Batch $0.75/$3.75; cached input $0.15/1M.
AgenticComputer useEfficientMultimodal1M context
Best for
Cost-efficient long-horizon agents and computer use
OpenAI's September 3, 2026 frontier release — the first GPT-6 model and OpenAI's answer to Claude Fable 5.1 two days earlier. State of the art on computer use (OSWorld 2.0 72.6% in ~47% less time than GPT-5.6 Sol), agentic coding (Terminal-Bench 4.0 57.9%), and frontier math (FrontierMath Tier 4 97.6%). $10/$50 per 1M tokens, 1.05M context, 128K output, knowledge cutoff April 30, 2026.
Verdict
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Quality score
99%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1.1M tokens
Released September 3, 2026. API ID gpt-6-astra; rolling out over the coming days to ChatGPT Plus, Pro, Business and Enterprise (usage inside existing allowances; GPT-6 Astra Pro for Pro/Business/Enterprise; Enterprise off by default), the OpenAI API, Microsoft Azure and Amazon Bedrock. Standard API pricing $10/$50 per 1M tokens; Fast mode is up to 2x speed at 2x price; cache reads and writes have separate rates. Model docs list 1,050,000 context, 128,000 max output, knowledge cutoff April 30, 2026, reasoning efforts up to 'max'. Published launch numbers (Astra / GPT-5.6 Sol / Fable 5.1 / Opus 5): OSWorld 2.0 72.6 / 65.7 / — / 70.2; Terminal-Bench 4.0 57.9 / 37.3 / 55.8 / 52.3; Terminal-Bench Science 0.1 64.6 / 22.4 / 52.6 / 30.0; FrontierMath Tier 4 v2 97.6 / 83.0 / 87.8 / 73.2; GPQA Diamond 96.0 / 94.6 / 93.7 / 93.7; Humanity's Last Exam w/ tools 57.2 / — / 65.0 / 63.6; AutomationBench 41.4 / 18.1 / 31.4 / 26.9; DeepSWE v1.1 74.1 / 72.7 / 67.4 / 73.7; ARC-AGI-2 95.0 / 92.5 / 90.0 / 90.4; ARC-AGI-3 99.9 (OpenAI responses-API harness; ARC Prize's stateless runs score far lower) / 7.8 / — / 30.2; ExploitBench 100.0 / 78.5 / — / 70; SRE-Bench 88.0 / 55.9; Artificial Analysis Intelligence Index v4.1.1 61.2 / 60.9 / 65.7 / 63.1. Meets the Critical threshold for cybersecurity under OpenAI's Preparedness Framework; advanced cyber workflows gated behind OpenAI Daybreak. All figures from OpenAI's launch post and model docs, verified September 4, 2026.
Computer use leaderFrontierAgenticReasoningLong contextPremiumNew
Best for
Computer and browser use, long-horizon agentic coding, and frontier math and science work
Gemini 3.1 Pro costs $2 per million input tokens and $12 per million output tokens on the API, with cached input at $0.2 per million. A month of 10M input and 2M output tokens runs about $44.00 at list price, before any batch or caching discounts.
What is the context window of Gemini 3.1 Pro?
Gemini 3.1 Pro has a 1M tokens context window, with up to 64k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is the knowledge cutoff of Gemini 3.1 Pro?
Gemini 3.1 Pro's training data runs through January 2025, and the model was released on February 19, 2026. For anything after that date it needs web search or documents in the prompt.
What is Gemini 3.1 Pro best for?
Gemini 3.1 Pro is best for research, deep document analysis, and long-context reasoning at competitive pricing. It is a strong fit when that workflow matters more than the tradeoffs around premium pricing and balanced speed.
When should I avoid Gemini 3.1 Pro?
Your primary use case is writing quality or agentic coding — Claude wins both.
What is a cheaper alternative to Gemini 3.1 Pro?
Gemini 3.6 Flash (Google) at $0.75/1M/1M input against Gemini 3.1 Pro's $2.00/1M/1M — roughly 68% less per token all in. Best Gemini for agents — efficiency king with native computer use. Compare it first if Gemini 3.1 Pro's pricing is the thing stopping you.
What is a faster alternative to Gemini 3.1 Pro?
Gemini 3.5 Flash — fast against Gemini 3.1 Pro's balanced, with 1.0M tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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