MODEL RADAR · OPENROUTER
Compare modelos de IA com os mesmos critérios.
Todos os modelos atualmente listados pela OpenRouter, com dados consistentes sobre modalidades, contexto, preços, configuração e provedores.
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- modelos
- 631
- provedores
- 86
- última sincronização
- 29 de set. de 2026
openaiOpenAI: GPT-5.2 Pro (batch)
GPT-5.2 Pro is OpenAI’s most advanced model, offering major improvements in agentic coding and long context performance over GPT-5 Pro. It is optimized for complex tasks that require step-by-step reasoning,...
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- 400K
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openaiOpenAI: GPT-5.2
GPT-5.2 is the latest frontier-grade model in the GPT-5 series, offering stronger agentic and long context perfomance compared to GPT-5.1. It uses adaptive reasoning to allocate computation dynamically, responding quickly...
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- 400K
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openaiOpenAI: GPT-5.2 (batch)
GPT-5.2 is the latest frontier-grade model in the GPT-5 series, offering stronger agentic and long context perfomance compared to GPT-5.1. It uses adaptive reasoning to allocate computation dynamically, responding quickly...
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- 400K
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mistralaiMistral: Devstral 2 2512
Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. Devstral 2 supports exploring...
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- 262K
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relaceRelace: Relace Search
The relace-search model uses 4-12 viewfile and grep tools in parallel to explore a codebase and return relevant files to the user request. In contrast to RAG, relace-search performs agentic...
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- 256K
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z-aiZ.ai: GLM 4.6V
GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts...
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- 131K
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openrouterBody Builder (beta)
Transform your natural language requests into structured OpenRouter API request objects. Describe what you want to accomplish with AI models, and Body Builder will construct the appropriate API calls. Example:...
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- 128K
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openaiOpenAI: GPT-5.1-Codex-Max
GPT-5.1-Codex-Max is OpenAI’s latest agentic coding model, designed for long-running, high-context software development tasks. It is based on an updated version of the 5.1 reasoning stack and trained on agentic...
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- 400K
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amazonAmazon: Nova 2 Lite
Nova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text. Nova 2 Lite demonstrates standout capabilities in processing...
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- 1M
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mistralaiMistral: Ministral 3 14B 2512
The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language...
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- 262K
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mistralaiMistral: Ministral 3 8B 2512
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
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- 262K
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mistralaiMistral: Ministral 3 8B 2512 (batch)
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
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- 262K
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mistralaiMistral: Ministral 3 3B 2512
The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
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- 131K
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mistralaiMistral: Mistral Large 3 2512
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
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- 262K
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mistralaiMistral: Mistral Large 3 2512 (batch)
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
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- 262K
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deepseekDeepSeek: DeepSeek V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
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- 164K
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black-forest-labsBlack Forest Labs: FLUX.2 Flex
FLUX.2 [flex] excels at rendering complex text, typography, and fine details, and supports multi-reference editing in the same unified architecture. Pricing is as follows, per the docs: We charge $0.06...
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black-forest-labsBlack Forest Labs: FLUX.2 Pro
A high-end image generation and editing model focused on frontier-level visual quality and reliability. It delivers strong prompt adherence, stable lighting, sharp textures, and consistent character/style reproduction across multi-reference inputs....
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anthropicAnthropic: Claude Opus 4.5
Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and...
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- 200K
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anthropicAnthropic: Claude Opus 4.5 (batch)
Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and...
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- 200K
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googleGoogle: Nano Banana Pro (Gemini 3 Pro Image Preview)
Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...
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thenlperThenlper: GTE-Base
The gte-base embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, delivering efficient and effective semantic embeddings optimized for textual similarity, semantic search, and clustering applications.
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- 1K
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thenlperThenlper: GTE-Large
The gte-large embedding model converts English sentences, paragraphs and moderate-length documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for information retrieval, semantic textual similarity, reranking and...
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- 1K
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intfloatIntfloat: E5-Large-v2
The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic search, reranking, and similarity-scoring tasks.
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- 1K
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- embeddings