Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
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Google: Gemma 4 31B (batch) holds the #149 spot for context size out of 378 chat models in the CoreAI catalog — 262K tokens, roughly 196,608 words or 393 pages of text in a single conversation. On price, it is the #111 cheapest of 124 budget-tier models by input cost. It joined the catalog on 2026-04-02. It supports step-by-step reasoning (thinking mode) and accepts image input.
Every model in this table is available on CoreAI — open the web app and run the same prompt through Google: Gemma 4 31B (batch) and Google: Gemini 3.6 Flash (batch) side by side to judge with your own eyes.
A typical question (about 1,000 tokens in, 500 out) runs $0.00088 on Google: Gemma 4 31B (batch)'s raw per-token rates; a heavy session with a 50K-token document costs about $0.024. On CoreAI you don't juggle these numbers — one subscription covers Google: Gemma 4 31B (batch) and 300+ other models under a plan usage limit, with no API keys. See plans.
Google: Gemma 4 31B (batch) handles 262K tokens of context — roughly 196,608 words, or about 393 pages of text in one conversation.
Google: Gemma 4 31B (batch)'s underlying rates are $0.39 per 1M input tokens and $0.97 per 1M output tokens. On CoreAI it is included in one subscription alongside 300+ models, so there is no per-token billing to manage.
Yes — Google: Gemma 4 31B (batch) accepts image input, so you can attach screenshots, photos or diagrams and ask questions about them.
Yes. Google: Gemma 4 31B (batch) can work through problems step by step before answering; on CoreAI you can toggle thinking mode per message.
Open the CoreAI web app or the iOS/Android app, pick Google: Gemma 4 31B (batch) in the model selector, and chat — no API key, no per-token billing. One subscription covers Google: Gemma 4 31B (batch) and 300+ other models.
The closest alternatives on CoreAI are Google: Gemini 3.6 Flash (batch), Ling 3.0 Flash Fin (free), IBM: Granite 4.0 Micro — similar capability. The fastest way to choose is running one prompt through them side by side in CoreAI's Compare view.
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