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2,832 models1,623 with prices34 metricsUpdated Oct 21, 2026 ↗

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nex-agiListed Sep 8

Nex AGI: Nex-N2.5-Mini

Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...

262.1K contextImage inputStructured outputNo reported score
No reported score
$0.025in$0.10out/ 1M tokens · USDNex AGI · via OpenRouter · 2 endpointsnex-agi/bf16 · quantization=bf16
nex-agiListed Sep 8

Nex AGI: Nex-N2.5-Pro

Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...

262.1K contextImage inputTool callingNo reported score
No reported score
$0.075in$0.25out/ 1M tokens · USDNex AGI · via OpenRouter · 2 endpointsnex-agi/fp8 · quantization=fp8
openaiListed Sep 4

OpenAI: GPT-6 Astra (batch)

GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular…

1.1M contextImage inputTool callingNo reported score
No reported score
$5.00in$25.00out/ 1M tokens · USDOpenAI · via OpenRouter · 2 endpointsopenai · prompt ≤ 272000 tokens
openaiListed Sep 4

OpenAI: GPT-6 Astra Pro

GPT-6 Astra Pro is the same underlying model as GPT-6 Astra, served with reasoning.mode set to pro for higher-quality responses on complex tasks. Cost note: pro mode spends far more...

1.1M contextImage inputTool callingNo reported score
No reported score
$5.00in$25.00out/ 1M tokens · USDOpenAI · via OpenRouter · 7 endpointsopenai/flex · tier=flex · prompt ≤ 272000 tokens
openaiListed Sep 4

OpenAI: GPT-6 Astra Pro (batch)

GPT-6 Astra Pro is the same underlying model as GPT-6 Astra, served with reasoning.mode set to pro for higher-quality responses on complex tasks. Cost note: pro mode spends far more...

1.1M contextImage inputTool callingNo reported score
No reported score
$5.00in$25.00out/ 1M tokens · USDOpenAI · via OpenRouter · 2 endpointsopenai · prompt ≤ 272000 tokens
inclusionAIListed Sep 4

Ling-3.0-flash-VL

The multimodal version built on Ling-3.0-flash — 124B total / ~5.5B active per token, with native text, image, and video understanding. It’s mainly designed for multimodal agentic workflows, long-context…

262.1K contextImage inputVideo inputNo reported score
No reported score
$0.06in$0.18out/ 1M tokens · USDDeepInfra · 4 endpoints
qwenListed Sep 3

Qwen: Qwen3.8 Max (0902)

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...

1M contextImage inputVideo inputNo reported score
No reported score
$2.00in$6.00out/ 1M tokens · USDAlibaba · via OpenRouter · 3 endpointsalibaba/us-east-1
microsoftListed Sep 3

Microsoft AI: MAI-Transcribe 2

MAI-Transcribe 2 is a multilingual speech-to-text model from Microsoft AI, ranked #1 on the FLEURS multilingual benchmark. It supports 60 languages with automatic language identification, code switching for…

Audio inputNo reported score
No reported score
$100,000.00in$0.00out/ 1M tokens · USDOpenRouter
metaListed Sep 2

Meta: Muse Spark 1.3 Contributor

Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is…

1M contextImage inputVideo inputNo reported score
No reported score
$0.10in$0.20out/ 1M tokens · USDMeta · via OpenRouter · 2 endpointsmeta
metaListed Sep 2

Meta: Muse Spark 1.3

Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through...

1M contextImage inputVideo inputNo reported score
No reported score
$1.25in$4.25out/ 1M tokens · USDMeta · via OpenRouter · 2 endpointsmeta
googleListed Sep 2

Google: Gemini 3.8 Flash

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

1M contextImage inputAudio inputNo reported score
No reported score
$0.375in$1.875out/ 1M tokens · USDGoogle AI Studio · via OpenRouter · 9 endpointsgoogle-ai-studio/flex · tier=flex
googleListed Sep 2

Google: Gemini 3.8 Flash (batch)

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

1M contextImage inputAudio inputNo reported score
No reported score
$0.375in$1.875out/ 1M tokens · USDGoogle · via OpenRouter · 2 endpointsgoogle-vertex/global
anthropicListed Sep 1

Anthropic: Claude Fable 5.1 (batch)

Claude Fable 5.1 improves on Claude Fable 5 across the board, with the biggest gains in agentic coding, long-running agentic workflows, and knowledge work: long code refactors, front-end and visual...

1M contextImage inputTool callingNo reported score
No reported score
$5.00in$25.00out/ 1M tokens · USDAnthropic · via OpenRouter · 2 endpointsanthropic
xaiListed Aug 28

Grok Voice

Build real-time voice applications powered by Grok. Stream audio and text bidirectionally via WebSocket for voice assistants, phone agents, and interactive voice systems.

No reported score
No reported score
Listed from $0.00083/ second · USDfal
xaiListed Aug 27

Grok Voice

Build real-time voice applications powered by Grok. Send recorded audio and get a voice and text response.

No reported score
No reported score
Listed from $0.00083/ second · USDfal
briaListed Aug 27

Video

Remove background from videos filmed using chromakey, with automatic green spill suppression for clean, professional edges.

No reported score
No reported score
Listed from $0.05/ second · USDfal
tencentListed Aug 27

Hy4-preview

Hy4 preview is a 770B-parameter Mixture-of-Experts flagship model from the Tencent Hy Team, with 49B parameters activated per token and a 1M-token context window. It uses Gated DeepSeek Sparse Attention…

1M contextTool callingStructured outputNo reported score
No reported score
$0.834in$2.501out/ 1M tokens · USDdeepinfra · via Hugging Face · 8 endpoints