# Gemini 3 Pro: pricing, crowd verdict, pros and cons (2026)

> Google's Nov 2025 frontier model: 1M context, first past 1500 Elo on LMArena, replaced by Gemini 3.1 Pro.

Source: [GLAD-AI-TOR](https://glad-ia-tor.com) · Full page: https://glad-ia-tor.com/tool/gemini-3-pro
Arena: llm-models · Crowd score: 57% recommend (3 votes, Bayesian-smoothed) · Price: $12/1M out (prompts ≤200K)

Frontier reasoning model from Google DeepMind, released November 18, 2025. First model to break 1500 Elo on LMArena, with a 1M-token context window and native text, image, audio and video understanding. Retired March 9, 2026 in favor of Gemini 3.1 Pro at the same price.

## Key facts

- provider: Google (DeepMind)
- contextWindow: 1M tokens (64K output)
- priceIn: $2/1M in (prompts ≤200K)
- priceOut: $12/1M out (prompts ≤200K)
- modalities: text, image, audio, video in; text out
- openWeights: no

## Ratings (editorial, 1-5)

- reasoning: 4.5/5
- coding: 4.5/5
- writing: 3.5/5
- speed: 3.5/5
- valueForMoney: 4/5

## Pros

- Topped LMArena at launch with a record 1501 Elo and scored 91.9% on GPQA Diamond, state of the art at release
- ARC-AGI-2 at 31.1%, roughly 6x Gemini 2.5 Pro (4.9%) and nearly double GPT-5.1 (17.6%) at the time
- Best-in-class multimodal understanding: 81% MMMU-Pro, 87.6% Video-MMMU, with a 1M-token context window
- Strong agentic coding: 76.2% SWE-bench Verified, 54.2% Terminal-Bench 2.0, 1487 Elo on WebDev Arena
- Undercut rivals on price at $2/$12 per 1M tokens, below Claude Sonnet-class pricing ($3/$15)
- Configurable thinking_level (low/medium/high) lets developers trade reasoning depth against latency and cost

## Cons

- Overconfident hallucinations: on AA-Omniscience it gave a wrong answer 88% of the time instead of declining, vs 48% for Claude Sonnet 4.5 (the-decoder)
- Sycophancy widely reported by reviewers (Zvi Mowshowitz: 'vast intelligence with no spine'); needs tight system prompts
- Tool-calling reliability issues in agent stacks: devs reported tool outputs dumped into the chat thread and more scaffolding needed than OpenAI/Anthropic models
- Slow at high thinking level: time to first token measured around 30-60s on AI Studio despite ~130 tok/s output speed
- Retired: shut down on the Gemini API and AI Studio on March 9, 2026, with gemini-3-pro-preview now aliased to Gemini 3.1 Pro

## Best for

- multimodal analysis (video/audio/image)
- long-context reasoning
- agentic coding
- math and science reasoning

## Verdict

A landmark release that put Google back on top in late 2025, with a huge reasoning jump over Gemini 2.5 Pro and the best multimodal scores of its generation. As of mid-2026 there is no reason to choose it: Google shut it down on the API on March 9, 2026, and Gemini 3.1 Pro costs exactly the same while more than doubling ARC-AGI-2 performance (77.1% vs 31.1%). Teams on legacy deployments should migrate to 3.1 Pro, which the old model ID now points to anyway. Avoid it for hallucination-sensitive workloads unless you add grounding, a weakness reviewers flagged repeatedly.

## Pricing note

Standard tier: $2/$12 per 1M tokens for prompts ≤200K, $4/$18 above 200K; batch at 50% off. Retired March 9, 2026, successor Gemini 3.1 Pro keeps identical pricing.

## Alternatives and head-to-heads

- [Claude Haiku 4.5](https://glad-ia-tor.com/tool/claude-haiku-4-5) (crowd score 67%) · [Gemini 3 Pro vs Claude Haiku 4.5](https://glad-ia-tor.com/vs/gemini-3-pro-vs-claude-haiku-4-5)
- [Claude Fable 5](https://glad-ia-tor.com/tool/claude-fable-5) (crowd score 63%) · [Gemini 3 Pro vs Claude Fable 5](https://glad-ia-tor.com/vs/gemini-3-pro-vs-claude-fable-5)
- [Claude Opus 4.7](https://glad-ia-tor.com/tool/claude-opus-4-7) (crowd score 57%) · [Gemini 3 Pro vs Claude Opus 4.7](https://glad-ia-tor.com/vs/gemini-3-pro-vs-claude-opus-4-7)
- [Claude Sonnet 5](https://glad-ia-tor.com/tool/claude-sonnet-5) (crowd score 57%) · [Gemini 3 Pro vs Claude Sonnet 5](https://glad-ia-tor.com/vs/gemini-3-pro-vs-claude-sonnet-5)

Full ranking: https://glad-ia-tor.com/hall-of-fame/llm-models

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