Claude 3 Haiku vs Gemini 3.5 Flash-Lite
Compare Claude 3 Haiku and Gemini 3.5 Flash-Lite side-by-side. See how these vision models stack up in Open Prompt, OCR, Image Captioning, Object Detection, and Classification.
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Claude 3 Haiku is deprecated and can no longer be run. Details and evals are still available on its model page.
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Claude 3 Haiku vs Gemini 3.5 Flash-Lite Comparison Table
Evals updated August 6, 2026Pricing updated August 10, 2026
| Property | Claude 3 Haiku | Gemini 3.5 Flash-Lite |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Mar 2024 | Jul 2026 |
| Context Window | 200K | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.300 | |
| Output $/1M | $2.50 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Video Classification | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | Deprecated | 69.6% |
| Avg cost / sample | – | $0.0014 |
| Avg speed / sample | – | 2.70s |
| By task | ||
| Object Detection | – | 57.5% $0.0023 |
| Counting | – | 52.7% $0.0007 |
| Identification | – | 81.3% $0.0004 |
| OCR | – | 87.4% $0.0011 |
| Data Extraction | – | 90.7% $0.0004 |
| Reasoning (low) | – | 48.3% $0.0012 |
| Reasoning (high) | – | 68.9% $0.0042 |
Claude 3 Haiku vs Gemini 3.5 Flash-Lite: Overview
Claude 3 Haiku is a large language model developed by Anthropic and released in March 2024 as part of the Claude 3 family, alongside Claude 3 Sonnet and Claude 3 Opus. It is designed to be the fastest and most cost-efficient model in the series, optimized for high-throughput applications.
Like the other Claude 3 models, Haiku is multimodal, able to process both text and image inputs while generating text outputs. It supports a context window of up to 200,000 tokens, with Anthropic noting that the Claude 3 models are technically capable of handling inputs exceeding one million tokens in special cases.
Haiku is positioned as a model well-suited for scenarios that demand speed and scalability at lower cost, such as customer support, summarization, and other tasks where rapid responses are prioritized. Compared to the larger Claude 3 Sonnet and Opus, Haiku provides lower latency and higher efficiency, while the larger models offer stronger reasoning and depth of analysis.
Gemini 3.5 Flash-Lite is a natively multimodal reasoning model developed by Google DeepMind, released on July 21, 2026 as part of the Gemini 3.5 model family. It is the fastest model in the 3.5 series, designed for both low-latency tasks and high-throughput production workloads such as agentic search, document processing, receipt translation, and large-scale data extraction. The model accepts text, images, audio, and video as inputs, with a context window of up to 1 million tokens, and produces text output. It supports configurable thinking levels, allowing developers to tune the balance between response quality, cost, and latency depending on workload requirements.
On agentic and coding benchmarks, Gemini 3.5 Flash-Lite significantly outperforms its predecessor, Gemini 3.1 Flash-Lite, including on Terminal-Bench 2.1 (54% vs. 31%), GDM-MRCR v2 long-context (72.2% vs. 60.1%), and real-world task execution as measured by GDPval-AA v2 (1140 vs. 642). It also surpasses Gemini 3 Flash on SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 65.1%). According to the Artificial Analysis Index, the model generates output at approximately 350 tokens per second. It is built on the Gemini 3.5 Flash foundation and is evaluated across reasoning, coding, multimodal understanding, multilingual performance, and long-context tasks. The model is developed under Google's Frontier Safety Framework.