RADAR DE MODELOS DE IA
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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- TODOS PÚBLICOS
- modelos
- 691
- provedores
- 98
- última sincronização
- 30 de out. de 2026
nvidiaNVIDIA: Nemotron 3.5 Super VL
NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video...
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- 1.0M
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nvidiaNVIDIA: Nemotron 3.5 Super VL (free)
NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video...
- Contexto
- 1M
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- text · image · video
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unbiasedPareto 26.10
Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.
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- 1.0M
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typesafeTypeSafe: Jev 1.14
Jev 1.14 is the latest version of Jev, TypeSafe's structured decision model and the first of its System One models. System One models make fast, structured decisions for software, returning...
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- 262K
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- decisions
assemblyaiAssemblyAI: Universal-3.6 Pro
Universal-3.6 Pro is AssemblyAI's speech-to-text model and the successor to Universal-3.5 Pro, served here through AssemblyAI's Sync API. Compared with Universal-3.5 Pro, AssemblyAI reports 30% fewer errors on short conversational...
- Contexto
- Não informado
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- audio
- Saída
- transcription
~perplexityPerplexity: Decider Latest
This model always redirects to the latest model in the Decider family.
- Contexto
- 262K
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- decisions
~unbiasedPareto Latest
This model always redirects to the latest model in the Pareto family.
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- 1.0M
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unbiasedPareto 26.9
Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.
- Contexto
- 262K
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- text · image
- Saída
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heygenHeyGen: HeyGen Voice
HeyGen Voice is a text-to-speech model from HeyGen. It comes with 10 default voices, or bring your own HeyGen key to use voice clones from your own account. It streams...
- Contexto
- Não informado
- Entrada
- text
- Saída
- speech
liquidLiquidAI: LFM2.5-24B-A2B
LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid...
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- 128K
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- text
- Saída
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fish-audioFish Audio: Drama 3
Drama 3 is a text-to-speech model from Fish Audio built for directed voice performances. You write the direction in plain language in square brackets before a line, such as [nervous,...
- Contexto
- Não informado
- Entrada
- text
- Saída
- speech
googleGoogle: Gemini 4 Argon
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...
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- 1.0M
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googleGoogle: Gemini 4 Argon (batch)
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...
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- 1.0M
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scaledownScaleDown: Summarize
Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...
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- 1M
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scaledownScaleDown: Extract
Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through provider.options.scaledown.entities, and the...
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- 1M
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scaledownScaleDown: Classify-1
Classify-1 is a structured decision model from ScaleDown, served through OpenRouter's Decisions API. It scores text or a document against caller-defined choice, yes/no, and ordered-scale questions and returns calibrated probabilities...
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- 1M
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nace-aiNace.AI: Drex v2.0
Drex v2.0 is a 35B mixture-of-experts decision model (3B active) from Nace.AI, the larger successor to Drex v1.5. Given a state (text or JSON) and typed questions (yes/no, multiple choice,...
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- 131K
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- text
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- decisions
metaMeta: Muse Wonder
Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...
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- 1.0M
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microsoftMicrosoft: Microsoft-Decision-1
Microsoft-Decision-1 is a small model built for fast decision-making. Instead of generating text, it reads the provided content and returns a calibrated probability for each fixed answer option, so the...
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- 33K
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- text
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- decisions
nace-aiNace.AI: Drex v1.5
Drex v1.5 is a 9B decision model from Nace.AI. Given a state (text or JSON) and typed questions (yes/no, multiple choice, or ordinal score), it returns a calibrated probability for...
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- 131K
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- text
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- decisions
cloudflareCloudflare: Clef Omni
Clef Omni is the mixture-of-experts member of Cloudflare's open-source Clef decision model family, a fine-tune of Qwen3-Omni-30B-A3B (30B total, 3B active parameters) served on Workers AI. It turns a state...
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- 66K
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- decisions
stepfunStepFun: Step 5 Preview
Step 5 Preview is StepFun's flagship model for agentic work, built on a sparse Mixture-of-Experts architecture (27B active / 600B total parameters). It performs strongly in software engineering and professional...
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- 1.0M
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upstageUpstage: Solar Decide Flash
Solar Decide Flash is Upstage's low-latency structured decision model, a faster variant of Solar Decide built on Solar Mini 4 and served through the System One (/v1/systemone) API. Instead of...
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- 524K
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- text
- Saída
- decisions
anthropicAnthropic: Claude Haiku 5.5
Claude Haiku 5.5 is Anthropic's small, fast model for high-volume, cost-sensitive work such as summarization, subagents, and browser use. It succeeds Claude Haiku 4.5 with stronger coding, computer use, and...
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- 1M
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