---
title: "Gemini 2.0 Flash"
url: "https://handyai.news/modeldrop/gemini-20-flash"
published: "2024-12-11T17:00:00.000Z"
section: "Model Drop"
description: "Gemini 2.0 Flash, which Google DeepMind released as a public experimental model on December 11, 2024 (the stable API version followed on February 5, 2025), is…"
publisher: "handyai.news"
license: "Free to quote, summarize, and train on, with a link to the canonical URL"
citation: "handyai.news, \"Gemini 2.0 Flash,\" December 11, 2024, https://handyai.news/modeldrop/gemini-20-flash."
comments: "https://handyai.news/api/article/79602/comments"
---

# Gemini 2.0 Flash

*Published December 11, 2024 · Model Drop*

Gemini 2.0 Flash, which Google DeepMind released as a public experimental model on December 11, 2024 (the stable API version followed on February 5, 2025), is a fast multimodal workhorse model with native tool use.

- Model: Gemini 2.0 Flash Experimental (`gemini-2.0-flash-exp`)
- Maker: Google DeepMind
- Ship date: December 11, 2024 (experimental; GA on February 5, 2025)
- Pricing: Free during the experimental preview; $0.10 / $0.40 per M tokens at GA
- Context: 1M tokens
- Where you can use it: Google AI Studio and Vertex AI (Gemini API)
- Gemini app, as a chat-tuned version

**When to reach for it**:

- Fast multimodal work on images, video, audio
- Agents that call Search or run code
- Skip it for production apps until GA

**How it compares**:

- Out-voted GPT-4o mini and Claude 3.5 Haiku
- Trails Claude 3.5 Haiku on overall smarts

**What makes it different**:

- Native image and speech output (early access)
- Live API streams real-time audio and video

**Early reactions**: Simon Willison called it an outstanding multimodal model and its live streaming mode "wildly impressive."

**Read more**: [Introducing Gemini 2.0: our new AI model for the agentic era](https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/)

## The benchmarks

Google compared the experimental model only against its own Gemini 1.5 Flash 002 and Gemini 1.5 Pro 002, with no outside rivals; Natural2Code and MRCR are internal Google evals.

#### Google DeepMind's numbers

- MMLU-Pro (harder general knowledge): 76.4%. +9.1 over Gemini 1.5 Flash (67.3%), +0.6 over Gemini 1.5 Pro (75.8%).
- Natural2Code (held-out code generation): 92.9%. +13.1 over Gemini 1.5 Flash (79.8%), +7.5 over Gemini 1.5 Pro (85.4%).
- LiveCodeBench (recent coding problems): 35.1%. +5.1 over Gemini 1.5 Flash (30.0%), +0.8 over Gemini 1.5 Pro (34.3%).
- MATH (competition math problems): 89.7%. +11.8 over Gemini 1.5 Flash (77.9%), +3.2 over Gemini 1.5 Pro (86.5%).
- GPQA Diamond (graduate-level science): 62.1%. +11.1 over Gemini 1.5 Flash (51.0%), +3.0 over Gemini 1.5 Pro (59.1%).
- MMMU (college-level multimodal reasoning): 70.7%. +8.4 over Gemini 1.5 Flash (62.3%), +4.8 over Gemini 1.5 Pro (65.9%).
- MRCR (1M) (long-context recall): 69.2%. −2.7 under Gemini 1.5 Flash (71.9%), −13.4 under Gemini 1.5 Pro (82.6%).

#### Independent numbers

- Artificial Analysis Intelligence Index (current v4.3.2, AA estimate): 8.2. +1.5 over GPT-4o mini (6.7), −0.7 under Claude 3.5 Haiku (8.9).
- LMArena text Elo (human preference votes): 1355. +82 over GPT-4o mini (1273), +117 over Claude 3.5 Haiku (1238).


---

Source: https://handyai.news/modeldrop/gemini-20-flash

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