about
OpenAI's most capable model for professional knowledge work, with improved spreadsheet creation, code generation, image perception, and multi-step project handling.
Licensegoogle
Context window(in thousands)1,048,576
Use cases for Gemini-2.0-Flash
- Multimodal intake processing: Native text, image, audio, and video input in a single model enables unified pipelines for processing mixed-media documents, recordings, and visual data.
- Million-token context analysis: The 1M-token window processes entire codebases, book-length documents, or multi-hour transcripts without chunking or retrieval augmentation.
- Tool-augmented generation: Native tool use allows it to execute code, query APIs, and perform calculations within its reasoning flow, suited for agentic applications that require real-world interaction.
Quality
Arena Elo1360
MMLUN/A
MT BenchN/A
Gemini 2.0 Flash scores 76.4% on MMLU and 78.9% on HumanEval, placing it between GPT-3.5 Turbo (70.0% MMLU) and GPT-4o mini (82.0% MMLU) on the same sheet. As a dense (non-MoE) model, it delivers consistent low-latency inference with a 1M-token context window, though its MMLU score trails the Gemini 2.5 Flash family that replaced it.
pricing
Running Gemini 2.0 Flash through Telnyx Inference costs $0.10 per million input tokens and $0.40 per million output tokens. Processing 10,000,000 multimodal requests at 500 tokens each would cost approximately $2,500, making it one of the most cost-effective models for high-volume text, image, and audio workloads.
What's Twitter saying?
- A 20-year developer praises Gemini 2.0 Flash for its value in coding, consistency in sticking to specified frameworks like Svelte, and significant API cost reductions, adding it to their daily primary models despite some struggles with complex components.
- Another developer finds results mixed and painful for daily coding after hours of testing the experimental version, deeming it not reliable enough compared to DeepSeek despite being impressive a year ago.
- Tech reviewers note superior speed and clarity over Gemini 1.5, with better creativity and logic in responses, making it a strong production choice for bang-for-buck despite not being perfect.
Explore Our LLM Library
Discover the power and diversity of large language models available with Telnyx. Explore the options below to find the perfect model for your project.
| Organization | Model Name | Tasks | Languages Supported | Context Length | Parameters | Model Tier | License |
|---|---|---|---|---|---|---|---|
| deepseek-ai | DeepSeek-R1-Distill-Qwen-14B | text generation | English | 43,000 | 14.8B | medium | deepseek |
| fixie-ai | ultravox-v0_4_1-llama-3_1-8b | audio text-to-text | Multilingual | 8,000 | 8.7B | small | mit |
| gemma-2b-it | text generation | English | 8,192 | 2.5B | small | gemma | |
| gemma-7b-it | text generation | English | 8,192 | 8.5B | small | gemma | |
| meta-llama | Llama-3.3-70B-Instruct | text generation | Multilingual | 99,000 | 70.6B | large | llama3.3 |
| meta-llama | Llama-Guard-3-1B | safety classification | Multilingual | 128,000 | 1.5B | small | llama3.3 |
| meta-llama | Meta-Llama-3.1-70B-Instruct | text generation | Multilingual | 99,000 | 70.6B | large | llama3.1 |
| meta-llama | Meta-Llama-3.1-8B-Instruct | text generation | Multilingual | 131,072 | 8.0B | small | llama3.1 |
| minimaxai | MiniMax-M2.5 | text generation | English | 2,000,000 | 0 | large | minimaxai |
| minimaxai | MiniMax-M2.7 | text generation | English | 200,000 | 0 | large | minimaxai |
| mistralai | Mistral-7B-Instruct-v0.1 | text generation | English | 8,192 | 7.2B | small | apache-2.0 |
| mistralai | Mistral-7B-Instruct-v0.2 | text generation | English | 32,768 | 7.2B | small | apache-2.0 |
| mistralai | Mixtral-8x7B-Instruct-v0.1 | text generation | Multilingual | 32,768 | 46.7B | medium | apache-2.0 |
| moonshotai | Kimi-K2.5 | text generation | English | 256,000 | 1.0T | large | modified-mit |
| Qwen | Qwen3-235B-A22B | text generation | English | 32,768 | 235.1B | large | apache-2.0 |
| zai-org | GLM-5.1-FP8 | text generation | English | 202,752 | 753.9B | large | mit |
| anthropic | claude-3-7-sonnet-latest | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| anthropic | claude-haiku-4-5 | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| anthropic | claude-opus-4-6 | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| anthropic | claude-sonnet-4-20250514 | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| gemini-2.0-flash | text generation | Multilingual | 1,048,576 | 0 | large | ||
| gemini-2.5-flash | text generation | Multilingual | 1,048,576 | 0 | large | ||
| gemini-2.5-flash-lite | text generation | Multilingual | 1,048,576 | 0 | large | ||
| groq | gpt-oss-120b | text generation | English | 131,072 | 117.0B | large | groq |
| groq | kimi-k2-instruct | text generation | English | 131,072 | 1.0T | large | groq |
| groq | llama-3.3-70b-versatile | text generation | Multilingual | 131,072 | 70.6B | large | llama3.3 |
| groq | llama-4-maverick-17b-128e-instruct | text generation | Multilingual | 1,000,000 | 400.0B | large | llama4 |
| groq | llama-4-scout-17b-16e-instruct | text generation | Multilingual | 128,000 | 109.0B | large | llama4 |
| openai | gpt-3.5-turbo | text generation | Multilingual | 4,096 | 0 | large | openai |
| openai | gpt-4 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-0125-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-0314 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-0613 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-1106-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-32k-0314 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-turbo-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4.1 | text generation | Multilingual | 1,047,576 | 0 | large | openai |
| openai | gpt-4.1-mini | text generation | Multilingual | 1,047,576 | 0 | large | openai |
| openai | gpt-4o | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4o-mini | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-5 | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | gpt-5-mini | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | gpt-5.1 | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | gpt-5.2 | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | o1-mini | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | o1-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | o3-mini | text generation | Multilingual | 200,000 | 0 | large | openai |
| xai-org | grok-2 | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-2-latest | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3 | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-beta | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-fast | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-fast-beta | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-fast-latest | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-latest | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-mini | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-mini-fast | text generation | Multilingual | 131,072 | 0 | large | xai |
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faqs
Is Gemini 2.0 Flash any good?
Gemini 2.0 Flash delivers strong performance across text, code, and multimodal tasks with native tool use capabilities. It features a 1 million token context window and is considered one of the most capable fast-response models available.
Is Gemini 2.0 Flash free?
Gemini 2.0 Flash is available for free through Google AI Studio with rate limits. Through the API, it has a free tier and paid pricing based on token usage. It is also accessible through Vertex AI for enterprise deployments.
Is Gemini 2.0 Flash being discontinued?
Gemini 2.0 Flash remains available, though Google has released newer models like Gemini 2.5 Flash and Flash-Lite. The 2.0 Flash model continues to be supported in the API alongside the newer versions.
How much does Gemini 2.0 Flash cost?
Gemini 2.0 Flash offers competitive pricing through Google's API, with rates varying by usage tier. For detailed pricing, Google's documentation provides current rates based on input and output tokens.
Is Gemini 2.0 Flash better than ChatGPT?
Gemini 2.0 Flash and ChatGPT (GPT-4o) have different strengths. Gemini 2.0 Flash offers a larger 1M token context window and native tool use, while GPT-4o has broader multimodal capabilities including audio. Performance varies by task.