コスト効率向けAIモデル

A lower-cost GPT-5.6 model for high-volume chat, classification and lightweight agent workflows.

コンテキスト

1.05M

入力

$0.20

出力

$1.2

A fast multimodal Gemini model listed for responsive agent workflows, coding and multi-step reasoning.

コンテキスト

1.05M

入力

$0.375

出力

$1.88

An open-weight vision-language model listed for coding, research, multimodal interaction and agent tasks.

コンテキスト

262K

入力

$0.45

出力

$3.2

An open-weight coding model listed for coding agents and local development workflows.

コンテキスト

262K

入力

$0.12

出力

$0.80

Runway Aleph 2.0 is an in-context video editing model from Runway. It applies text instructions and keyframe-guided edits across existing footage while preserving details that are not meant to change.…

コンテキスト

0

入力

$0.00

出力

$0.00

Sentence Transformers: all-MiniLM-L12-v2 is included in the AIToolly model catalog.

コンテキスト

512

入力

$0.005

出力

$0.00

Sentence Transformers: all-MiniLM-L6-v2 is included in the AIToolly model catalog.

コンテキスト

512

入力

$0.005

出力

$0.00

Sentence Transformers: all-mpnet-base-v2 is included in the AIToolly model catalog.

コンテキスト

512

入力

$0.005

出力

$0.00

If you are looking for a model that supports more languages, longer texts, and other retrieval methods, you can try using bge-m3.

コンテキスト

512

入力

$0.005

出力

$0.00

If you are looking for a model that supports more languages, longer texts, and other retrieval methods, you can try using bge-m3.

コンテキスト

512

入力

$0.01

出力

$0.00

In this project, we introduce BGE-M3, which is distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.

コンテキスト

8K

入力

$0.01

出力

$0.00

Mistral Codestral Embed is specially designed for code, perfect for embedding code databases, repositories, and powering coding assistants with state-of-the-art retrieval.

コンテキスト

8K

入力

$0.15

出力

$0.00

> I have to praise this model for good focus. I said earlier that it still remembers it at 12K. I think my personal evaluation of it has already beaten the rest.

コンテキスト

131K

入力

$0.30

出力

$0.50

We introduce **DeepSeek-V3.2**, a model that harmonizes high computational efficiency with superior reasoning and agent performance. Our approach is built upon three key technical breakthroughs:

コンテキスト

164K

入力

$0.269

出力

$0.40

We are excited to announce the official release of DeepSeek-V3.2-Exp, an experimental version of our model. As an intermediate step toward our next-generation architecture, V3.2-Exp builds upon V3.1-Terminus by introducing DeepSeek Sparse Attention—a sparse attention mechanism designed to explore and validate optimizations for training and inference efficiency in long-context scenarios.

コンテキスト

164K

入力

$0.27

出力

$0.41

We present a preview version of **DeepSeek-V4** series, including two strong Mixture-of-Experts (MoE) language models — **DeepSeek-V4-Pro** with 1.6T parameters (49B activated) and **DeepSeek-V4-Flash** with 284B parameters (13B activated) — both supporting a context length of **one million tokens**.

コンテキスト

1.02M

入力

$0.0826

出力

$0.1652

**DeepSeek-V4-Flash-0731** is the official release of **DeepSeek-V4-Flash**, superseding the preview version, with substantially enhanced agentic capabilities. It has the same model structure as DeepSeek-V4-Flash-DSpark, i.e. it comes with a speculative decoding module attached.

コンテキスト

1.05M

入力

$0.14

出力

$0.28

This model always redirects to the latest model in the DeepSeek V4 Flash family.

コンテキスト

1.02M

入力

$0.0786

出力

$0.1572

Dots3-Note Preview is an open-weight mixture-of-experts model from Dots Studio, with 16B active parameters out of 280B total. It is the lightest model in the Dots 3 family and is…

コンテキスト

512K

入力

$0.00

出力

$0.00

Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022

コンテキスト

512

入力

$0.005

出力

$0.00

Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022

コンテキスト

512

入力

$0.01

出力

$0.00

pplx-embed-v1-0.6B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized for standard dense text retrieval with the 0.6B parameter model targeting lightweight, low-latency…

コンテキスト

32K

入力

$0.004

出力

$0.00

pplx-embed-v1 -4B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized for standard dense text retrieval with the 4B parameter model maximizing retrieval…

コンテキスト

32K

入力

$0.03

出力

$0.00

Flux TTS is a text-to-speech model from Deepgram. It is suited for natural, expressive English speech synthesis across Deepgram's Flux voice catalog.

コンテキスト

0

入力

$0.00

出力

$0.00

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…

コンテキスト

67K

入力

$0.00

出力

$0.00

The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, **delivering state-of-the-art quality with end-to-end inference in as low as under a second**. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM.

コンテキスト

41K

入力

$0.00

出力

$0.00

FLUX.2 [max] is the new top-tier image model from Black Forest Labs, pushing image quality, prompt understanding, and editing consistency to the highest level yet. Pricing is as follows, [per…

コンテキスト

47K

入力

$0.00

出力

$0.00

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.…

コンテキスト

47K

入力

$0.00

出力

$0.00

FLUX.3 Video is a video generation model from Black Forest Labs. It supports text-to-video, image-guided generation with opening and closing keyframes, and video continuation workflows, making it suited for controlled…

コンテキスト

0

入力

$0.00

出力

$0.00

The simplest way to get free inference. the provider catalog/free is a router that selects free models at random from the models available on the provider catalog. The router smartly filters for models that…

コンテキスト

200K

入力

$0.00

出力

$0.00

gemini-embedding-001 provides a unified cutting edge experience across domains, including science, legal, finance, and coding. This embedding model has consistently held a top spot on the Massive Text Embedding Benchmark…

コンテキスト

20K

入力

$0.15

出力

$0.00

Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It supports…

コンテキスト

8K

入力

$0.20

出力

$0.00

Gemini Embedding 2 Preview is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It…

コンテキスト

8K

入力

$0.20

出力

$0.00

Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages.

コンテキスト

262K

入力

$0.07

出力

$0.34

Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages.

コンテキスト

262K

入力

$0.10

出力

$0.34

Runway Gen-4.5 is a video generation model from Runway for text-to-video and image-to-video workflows. It is designed for cinematic scene creation with strong motion quality, visual fidelity, and prompt adherence.…

コンテキスト

0

入力

$0.00

出力

$0.00

GLM-4.7-Flash is a 30B-A3B MoE model. As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency.

コンテキスト

203K

入力

$0.06

出力

$0.40

gpt-oss-safeguard-120b and gpt-oss-safeguard-20b are safety reasoning models built-upon gpt-oss. With these models, you can classify text content based on safety policies that you provide and perform a suite of foundational safety tasks. These models are intended for safety use cases. For other applications, we recommend using gpt-oss models.

コンテキスト

131K

入力

$0.075

出力

$0.30

📣 **Update [10-07-2025]:** Added a *default system prompt* to the chat template to guide the model towards more *professional, accurate, and safe* responses.

コンテキスト

131K

入力

$0.017

出力

$0.112

**Model Summary:** Granite-4.1-8B is a 8B parameter long-context instruct model finetuned from *Granite-4.1-8B-Base* using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets. Granite 4.1 models have gone through an improved post-training pipeline, including supervised finetuning and reinforcement learning alignment, resulting in enhanced tool calling, instruction following, and chat capabilities.

コンテキスト

131K

入力

$0.05

出力

$0.10

Grok Imagine Image 2.0 is an image generation and editing model from xAI. It is suited for creating images from text prompts and editing images from references, with low and…

コンテキスト

66K

入力

$0.00

出力

$0.00

Grok Imagine Image Quality is SpaceXAI's fast, high-fidelity image generation and editing model. It accepts text prompts and optional reference images, producing photorealistic outputs at 1K or 2K across a…

コンテキスト

66K

入力

$0.00

出力

$0.00

Grok Imagine Video is SpaceXAI's fast, text-, image-, and reference-conditioned video generation model. It produces short videos (1–15 seconds, 24 fps) at 480p or 720p across seven aspect ratios -…

コンテキスト

0

入力

$0.00

出力

$0.00

Grok Imagine Video 1.5 is a video generation model from SpaceXAI. It creates videos from text prompts, with an optional starting image to guide the scene. It can direct subject…

コンテキスト

0

入力

$0.00

出力

$0.00

General Text Embeddings (GTE) model. Towards General Text Embeddings with Multi-stage Contrastive Learning

コンテキスト

512

入力

$0.005

出力

$0.00

General Text Embeddings (GTE) model. Towards General Text Embeddings with Multi-stage Contrastive Learning

コンテキスト

512

入力

$0.01

出力

$0.00

MiniMax H3 is a lightweight, open-weights video generation model from MiniMax. It is designed for precise multimodal editing and controlled content generation, including instruction-guided edits, text and brand rendering, and…

コンテキスト

0

入力

$0.00

出力

$0.00

Hailuo 2.3 is a video generation model from MiniMax. It accepts text prompts and reference images as input and generates video output, supporting both text-to-video and image-to-video workflows. It is…

コンテキスト

0

入力

$0.00

出力

$0.00

HappyHorse 1.0 is a video generation model from Alibaba. It generates short videos from a text prompt, a single starting image, or a set of reference images, with output up…

コンテキスト

0

入力

$0.00

出力

$0.00

HappyHorse 1.1 is a video generation model from Alibaba. It generates short videos from a text prompt, a single starting image, or a set of reference images, with output up…

コンテキスト

0

入力

$0.00

出力

$0.00

Hermes 4 70B is a frontier, hybrid-mode **reasoning** model based on Llama-3.1-70B by Nous Research that is aligned to **you**.

コンテキスト

131K

入力

$0.13

出力

$0.40

**Hy3** is a 295B-parameter Mixture-of-Experts (MoE) model with 21B active parameters and 3.8B MTP layer parameters, developed by the Tencent Hy Team. Following the Hy3 Preview launch in late April, we gathered feedback from 50+ products and scaled up post-training with higher quality data. Today, we introduce Hy3, which outperforms similar-size models and rivals flagship open-source models with 2-5x parameters. It also shows significant gains in utility across various products and productivity tasks.

コンテキスト

262K

入力

$0.132

出力

$0.528

**Hy3 preview** is a 295B-parameter Mixture-of-Experts (MoE) model with 21B active parameters and 3.8B MTP layer parameters, developed by the Tencent Hy Team. Hy3 preview is the first model trained on our rebuilt infrastructure, and the strongest we've shipped so far. It improves significantly on complex reasoning, instruction following, context learning, coding, and agent tasks.

コンテキスト

262K

入力

$0.18

出力

$0.60

KAT-Coder-Air V2.5 is a flagship-level Agentic Coding model that can directly hand over an entire issue or an entire business workflow to it, allowing it to autonomously locate and make…

コンテキスト

256K

入力

$0.15

出力

$0.60

Kokoro 82M is a lightweight, open-weight text-to-speech model from hexgrad. It converts text to speech across 8 languages (American and British English, Spanish, French, Hindi, Italian, Japanese, Portuguese, and Chinese)…

コンテキスト

4K

入力

$0.62

出力

$0.00

Krea 2 Large is Krea's high-capability image generation model, more than twice the size of Krea 2 Medium. Its lighter post-training gives images a rawer, more textured, and flexible character,…

コンテキスト

66K

入力

$0.00

出力

$0.00

Krea 2 Medium is Krea's balanced, cost-efficient image generation model and a practical starting point for a broad range of use cases. Its extensive post-training supports stable, consistent generations, with…

コンテキスト

66K

入力

$0.00

出力

$0.00

Krea 2 Medium Turbo is a distilled, speed-focused variant of Krea 2 Medium from Krea. It is designed for rapid iteration and graphic design exploration where fast generation is the…

コンテキスト

66K

入力

$0.00

出力

$0.00

Laguna S 2.1 is a 118B total parameter Mixture-of-Experts model with 8B activated parameters per token, designed for agentic coding and long-horizon work. It sits between Laguna XS 2.1 (33B-A3B) and Laguna M.1 (225B-A23B) in the Laguna series and shares the family recipe: a token-choice router with softplus gating over 256 routed experts plus one shared expert, grouped-query attention, and interleaved full/sliding-window attention.

コンテキスト

1.05M

入力

$0.09

出力

$0.18

Laguna XS 2.1 is a 33B total parameter Mixture-of-Experts model with 3B activated parameters per token designed for agentic coding and long-horizon work on a local machine. This model is an upgraded version of our Laguna XS.2 model with a +5.4% jump on SWE-bench Multilingual as well as stronger performance on terminal-style tasks.

コンテキスト

262K

入力

$0.06

出力

$0.12

LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or…

コンテキスト

128K

入力

$0.00

出力

$0.00

Ling-2.6-1T is an instant (instruct) model from inclusionAI and the company’s trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale. It uses a “fast…

コンテキスト

262K

入力

$0.075

出力

$0.625

Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency.…

コンテキスト

262K

入力

$0.01

出力

$0.03

🤗 Hugging Face    |   🤖 ModelScope    |   🐙 the provider catalog   

コンテキスト

262K

入力

$0.021

出力

$0.063

NVIDIA: Llama Nemotron Embed VL 1B V2 (free) is included in the AIToolly model catalog.

コンテキスト

131K

入力

$0.00

出力

$0.00

Llama Nemotron Rerank VL 1B V2 is a 1.7B multimodal reranking model from NVIDIA. It evaluates the relevance of document images and text against user queries, designed for vision RAG…

コンテキスト

10K

入力

$0.00

出力

$0.00

30 second duration clips are priced at $0.04 per clip. Lyria 3 is Google's family of music generation models, available through the Gemini API. With Lyria 3, you can generate…

コンテキスト

1.05M

入力

$0.00

出力

$0.00

Full-length songs are priced at $0.08 per song. Lyria 3 is Google's family of music generation models, available through the Gemini API. With Lyria 3, you can generate high-quality, 48kHz…

コンテキスト

1.05M

入力

$0.00

出力

$0.00

Mercury 2 is an extremely fast reasoning LLM, and the first reasoning diffusion LLM (dLLM). Instead of generating tokens sequentially, Mercury 2 produces and refines multiple tokens in parallel, achieving…

コンテキスト

128K

入力

$0.25

出力

$0.75

🤗 HuggingFace  | 📰 Blog  | 🎨 Xiaomi MiMo API Platform  | 🗨️ Xiaomi MiMo Studio  |

コンテキスト

1.05M

入力

$0.14

出力

$0.28

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 model with vision capabilities.

コンテキスト

262K

入力

$0.20

出力

$0.20

The smallest model in the Ministral 3 family, **Ministral 3 3B** is a powerful, efficient tiny language model with vision capabilities.

コンテキスト

131K

入力

$0.10

出力

$0.10

A balanced model in the Ministral 3 family, **Ministral 3 8B** is a powerful, efficient tiny language model with vision capabilities.

コンテキスト

262K

入力

$0.15

出力

$0.15

Mistral Embed is a specialized embedding model for text data, optimized for semantic search and RAG applications. Developed by Mistral AI in late 2023, it produces 1024-dimensional vectors that effectively…

コンテキスト

8K

入力

$0.10

出力

$0.00

Mistral Small 4 is a powerful hybrid model capable of acting as both a general instruction model and a reasoning model. It unifies the capabilities of three different model families—**Instruct**, **Reasoning** (previously called Magistral), and **Devstral**—into a single, unified model.

コンテキスト

262K

入力

$0.15

出力

$0.60

This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and was designed for **semantic search**. It has been trained on 215M (question, answer) pairs from diverse sources. For an introduction to semantic search, have a look at: SBERT.net - Semantic Search

コンテキスト

512

入力

$0.005

出力

$0.00

Multilingual E5 Text Embeddings: A Technical Report. Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024

コンテキスト

512

入力

$0.01

出力

$0.00

NVIDIA Nemotron 3 Embed 1B is an open text embedding model from NVIDIA, optimized for high-throughput, low-latency retrieval. It is suited for enterprise search, RAG, code retrieval, and agentic retrieval…

コンテキスト

33K

入力

$0.00

出力

$0.00

Nemotron-3-Nano-30B-A3B-BF16 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be configured through a flag in the chat template. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.

コンテキスト

262K

入力

$0.05

出力

$0.20

NVIDIA Nemotron 3 Nano Omni is a multimodal large language model that unifies video, audio, image, and text understanding to support enterprise-grade Q&A, summarization, transcription, and document intelligence workflows. It extends the Nemotron Nano family with integrated video+speech comprehension, Graphical User Interface (GUI), Optical Character Recognition (OCR), and speech transcription capabilities, enabling end-to-end processing of rich enterprise content such as meeting recordings, M&E assets, training videos, and complex business documents. NVIDIA Nemotron 3 Nano Omni was developed by NVIDIA as part of the Nemotron model family.

コンテキスト

256K

入力

$0.00

出力

$0.00

> Use temperature=1.0 and top_p=0.95 across **all tasks and serving backends** — reasoning, tool calling, and general chat alike.

コンテキスト

262K

入力

$0.085

出力

$0.40

NVIDIA: Nemotron 3.5 Content Safety (free) is included in the AIToolly model catalog.

コンテキスト

128K

入力

$0.00

出力

$0.00

NVIDIA Nemotron™ is a family of open models with open weights, training data, and recipes, delivering leading efficiency and accuracy for building specialized AI agents.

コンテキスト

262K

入力

$0.08

出力

$0.20

NVIDIA: Nemotron Nano 12B 2 VL (free) is included in the AIToolly model catalog.

コンテキスト

128K

入力

$0.00

出力

$0.00

NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.

コンテキスト

128K

入力

$0.00

出力

$0.00

🤗 Model &nbsp&nbsp | &nbsp&nbsp 🔀 the provider catalog (Enjoy two weeks free starting June 9!) &nbsp&nbsp | &nbsp&nbsp 💻 Github &nbsp&nbsp | &nbsp&nbsp 🧭 ModelScope &nbsp&nbsp | &nbsp&nbsp 🚀 Nex-AGI

コンテキスト

262K

入力

$0.025

出力

$0.10

North Mini Code is Cohere's first agentic coding model and the debut of its North family. A sparse mixture-of-experts model with 30B total parameters and 3B active, it is optimized…

コンテキスト

256K

入力

$0.00

出力

$0.00

We introduce Olmo 3, a new family of 7B and 32B models both Instruct and Think variants. Long chain-of-thought thinking improves reasoning tasks like math and coding.

コンテキスト

66K

入力

$0.15

出力

$0.50

Sentence Transformers: paraphrase-MiniLM-L6-v2 is included in the AIToolly model catalog.

コンテキスト

512

入力

$0.005

出力

$0.00

Qwen Image 3 is a unified image generation and editing model from Qwen. It supports precise rendering of text and details as small as 10px, along with a richer world…

コンテキスト

66K

入力

$0.00

出力

$0.00

Qwen Image 3 Pro is an image generation and editing model from Qwen. It supports precise rendering of text and details as small as 10px, along with richer world knowledge…

コンテキスト

66K

入力

$0.00

出力

$0.00

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining.

コンテキスト

33K

入力

$0.02

出力

$0.00

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining.

コンテキスト

33K

入力

$0.01

出力

$0.00

Qwen3 Reranker 8B is a text reranking model from Alibaba Cloud built on the Qwen3 architecture. It evaluates query-document pairs to produce relevance scores for use in retrieval and RAG…

コンテキスト

41K

入力

$0.00

出力

$0.00

Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date.

コンテキスト

131K

入力

$0.13

出力

$0.52

Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date.

コンテキスト

131K

入力

$0.104

出力

$0.416

Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date.

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131K

入力

$0.117

出力

$0.455

> [!Note] > This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. > > These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

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262K

入力

$0.10

出力

$0.15

The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the…

コンテキスト

1M

入力

$0.065

出力

$0.26

Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding, search, and computer interaction, with strengths in object recognition, spatial understanding, and real-world…

コンテキスト

1M

入力

$0.03

出力

$0.13

Recraft V3 is an image generation model from Recraft. It supports text and image inputs with image output at ~1K resolution across multiple aspect ratios. Supports the following image_config parameters:…

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66K

入力

$0.00

出力

$0.00

Recraft V4 is an image generation model from Recraft. It supports text and image inputs with image output at ~1K resolution across multiple aspect ratios. It delivers stronger compositional judgment,…

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66K

入力

$0.00

出力

$0.00

Recraft V4 Pro is an image generation model from Recraft. It supports text and image inputs with image output at ~2K resolution across multiple aspect ratios, double the resolution of…

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66K

入力

$0.00

出力

$0.00

Recraft V4 Pro Vector is the vector (SVG) variant of Recraft V4 Pro. It supports text and image inputs and produces vector image output across multiple aspect ratios at the…

コンテキスト

66K

入力

$0.00

出力

$0.00

Recraft V4 Vector is the vector (SVG) variant of Recraft V4. It supports text and image inputs and produces vector image output across multiple aspect ratios. Compared to the raster…

コンテキスト

66K

入力

$0.00

出力

$0.00

Recraft V4.1 is an image generation model from Recraft tuned for high aesthetics. It supports text and image inputs with image output at ~1K resolution across multiple aspect ratios, with…

コンテキスト

66K

入力

$0.00

出力

$0.00

Recraft V4.1 Pro is an image generation model from Recraft tuned for high aesthetics. It supports text and image inputs with image output at ~2K resolution across multiple aspect ratios…

コンテキスト

66K

入力

$0.00

出力

$0.00

Recraft V4.1 Pro Vector is the vector (SVG) variant of Recraft V4.1 Pro, tuned for high aesthetics. It supports text and image inputs and produces higher-resolution SVG image output across…

コンテキスト

66K

入力

$0.00

出力

$0.00

Recraft V4.1 Utility is a general-purpose image generation model from Recraft. It supports text and image inputs with image output at ~1K resolution across multiple aspect ratios, with typical generation…

コンテキスト

66K

入力

$0.00

出力

$0.00

Recraft V4.1 Utility Pro is a general-purpose image generation model from Recraft. It supports text and image inputs with image output at ~2K resolution across multiple aspect ratios — double…

コンテキスト

66K

入力

$0.00

出力

$0.00

Recraft V4.1 Vector is the vector (SVG) variant of Recraft V4.1, tuned for high aesthetics. It supports text and image inputs and produces SVG image output across multiple aspect ratios,…

コンテキスト

66K

入力

$0.00

出力

$0.00

**Reka Edge** is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to deliver industry-leading performance in image understanding, video analysis, object detection, and agentic tool-use.

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16K

入力

$0.10

出力

$0.10

Cohere's AI search foundation model for enhancing the relevance of information surfaced within search and RAG systems. Features a 32K context window, multilingual support across 100+ languages, no data pre-processing…

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33K

入力

$0.00

出力

$0.00

Cohere's AI search foundation model for enhancing the relevance of information surfaced within search and RAG systems. Features a 32K context window, multilingual support across 100+ languages, no data pre-processing…

コンテキスト

33K

入力

$0.00

出力

$0.00

Rerank v3.5 is designed to reorder search results for improved relevance. It supports multi-aspect and semi-structured data reranking over 100+ languages. Ideal for refining results from semantic or keyword search…

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4K

入力

$0.00

出力

$0.00

rerank-2.5 is a cutting-edge reranker optimized for quality, delivering a 7.94% improvement in retrieval accuracy over Cohere Rerank v3.5 across 93 datasets. It also outperformed Cohere Rerank v3.5 by 12.70%…

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32K

入力

$0.00

出力

$0.00

rerank-2.5-lite is a reranker optimized for both latency and quality, delivering a 7.16% improvement in retrieval accuracy over Cohere Rerank v3.5 across 93 datasets. It also outperformed Cohere Rerank v3.5…

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32K

入力

$0.00

出力

$0.00

Ring-2.6-1T is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational efficiency. It is optimized for coding agents, tool…

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262K

入力

$0.075

出力

$0.625

Riverflow V2 Fast is the fastest variant of Sourceful's Riverflow 2.0 lineup, best for production deployments and latency-critical workflows. The Riverflow 2.0 series represents SOTA performance on image generation and…

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8K

入力

$0.00

出力

$0.00

Riverflow V2 Pro is the most powerful variant of Sourceful's Riverflow 2.0 lineup, best for top-tier control and perfect text rendering. The Riverflow 2.0 series represents SOTA performance on image…

コンテキスト

8K

入力

$0.00

出力

$0.00

Riverflow V2.5 Fast is the speed-optimized variant of Sourceful's Riverflow 2.5 lineup, best for production deployments and latency-critical workflows. The Riverflow 2.5 series is a unified text-to-image and image-to-image family…

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33K

入力

$0.00

出力

$0.00

Riverflow V2.5 Pro is the most powerful variant of Sourceful's Riverflow 2.5 lineup, best for top-tier control and quality-sensitive outputs. The Riverflow 2.5 series is a unified text-to-image and image-to-image…

コンテキスト

33K

入力

$0.00

出力

$0.00

S2.1 Pro Free is the no-cost variant of Fish Audio S2.1 Pro, intended for testing, prototyping, and low-volume applications. It provides the same synthesis capabilities without production latency or availability…

コンテキスト

0

入力

$0.00

出力

$0.00

Seed 1.6 Flash is an ultra-fast multimodal deep thinking model by ByteDance Seed, supporting both text and visual understanding. It features a 256k context window and can generate outputs of…

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262K

入力

$0.075

出力

$0.30

Seed-2.0-mini targets latency-sensitive, high-concurrency, and cost-sensitive scenarios, emphasizing fast response and flexible inference deployment. It delivers performance comparable to ByteDance-Seed-1.6, supports 256k context, four reasoning effort modes (minimal/low/medium/high), multimodal understanding,…

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262K

入力

$0.10

出力

$0.40

ByteDance's next-generation audio-visual generation model with a 4.5B parameter Dual-Branch Diffusion Transformer architecture. Seedance 1.5 Pro generates video and audio simultaneously in a single unified pass — eliminating the timing…

コンテキスト

0

入力

$0.00

出力

$0.00

Seedance 2.0 is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It is particularly strong at preserving character consistency,…

コンテキスト

0

入力

$0.00

出力

$0.00

Seedance 2.0 Fast is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It prioritizes generation speed and lower cost…

コンテキスト

0

入力

$0.00

出力

$0.00

Seedance 2.0 Mini is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video with image, video, and audio inputs. It…

コンテキスト

0

入力

$0.00

出力

$0.00

Seedance 2.5 is a video generation model from ByteDance. It is suited for long-form storytelling, multimodal reference-based generation, video editing, and video extension. It supports first-frame and first-and-last-frame control, up…

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0

入力

$0.00

出力

$0.00

Seedream 4.5 is the latest in-house image generation model developed by ByteDance. Compared with Seedream 4.0, it delivers comprehensive improvements, especially in editing consistency, including better preservation of subject details,…

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4K

入力

$0.00

出力

$0.00

Seedream 5.0 Lite is an image generation model from ByteDance Seed. It is suited for professional visual creation that benefits from web-connected retrieval, complex-prompt comprehension, visual references, and broad knowledge…

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0

入力

$0.00

出力

$0.00

Seedream 5.0 Pro is an image generation and editing model from ByteDance Seed. It is suited for commercial visual-production workflows that require precise editing control, lifelike scenes, and natural rendering.

コンテキスト

0

入力

$0.00

出力

$0.00

Solar Pro 3 is Upstage's powerful Mixture-of-Experts (MoE) language model. With 102B total parameters and 12B active parameters per forward pass, it delivers exceptional performance while maintaining computational efficiency. Optimized…

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131K

入力

$0.15

出力

$0.60

Solar Pro 4 is Upstage's cost-efficient large language model, featuring a 524K context window. It is built for long-horizon tasks and agentic workflows, with strong capabilities in office productivity, document-intensive…

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524K

入力

$0.03

出力

$0.12

OpenAI's flagship video generation model, delivering production-quality video with physics-accurate motion, synchronized audio, and world-state persistence across shots. Sora 2 Pro follows intricate multi-shot instructions while maintaining consistent spatial relationships…

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0

入力

$0.00

出力

$0.00

Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parameters per token.…

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262K

入力

$0.10

出力

$0.30

text-embedding-3-large is OpenAI's most capable embedding model for both english and non-english tasks. Embeddings are a numerical representation of text that can be used to measure the relatedness between two…

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8K

入力

$0.13

出力

$0.00

text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces…

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8K

入力

$0.02

出力

$0.00

text-embedding-ada-002 is OpenAI's legacy text embedding model.

コンテキスト

8K

入力

$0.10

出力

$0.00

Google's state-of-the-art video generation model, built for maximum visual fidelity in final production cuts. Veo 3.1 generates high-quality 1080p video from text or image prompts with native synchronized audio —…

コンテキスト

0

入力

$0.00

出力

$0.00

Google's mid-tier video generation model balancing speed and quality. Veo 3.1 Fast generates high-quality video from text or image prompts with native synchronized audio, offering faster turnaround than Veo 3.1…

コンテキスト

0

入力

$0.00

出力

$0.00

Google's most cost-effective video generation model, designed for high-volume applications and rapid iteration. Veo 3.1 Lite generates 720p and 1080p video from text or image prompts with native synchronized audio…

コンテキスト

0

入力

$0.00

出力

$0.00

Kling Video O1 is a video generation model from Kuaishou. It supports text and image inputs with video output, enabling text-to-video and image-to-video workflows. It is suited for cinematic content…

コンテキスト

0

入力

$0.00

出力

$0.00

Kling v3.0 Pro is Kuaishou's premium video generation model, offering higher visual quality than the Standard tier. It supports text-to-video and image-to-video workflows, with first-frame and last-frame control for precise…

コンテキスト

0

入力

$0.00

出力

$0.00

Kling v3.0 Standard is a video generation model from Kuaishou. It supports text-to-video and image-to-video workflows, with first-frame and last-frame control for guided scene composition. Clips range from 3 to…

コンテキスト

0

入力

$0.00

出力

$0.00

Voxtral Small is an enhancement of Mistral Small 3, incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding.

コンテキスト

32K

入力

$0.10

出力

$0.30

voyage-4 is a general-purpose (including multilingual) embedding model optimized for retrieval/search and AI applications. voyage-4 supports embeddings in 2048, 1024, 512, and 256 dimensions, with multiple quantization options. Learn more…

コンテキスト

32K

入力

$0.06

出力

$0.00

voyage-4-large is a state-of-the-art general-purpose and multilingual embedding optimized for retrieval quality. Enabled by Matryoshka learning and quantization-aware training, voyage-4-large supports embeddings in 2048, 1024, 512, and 256 dimensions, with…

コンテキスト

32K

入力

$0.12

出力

$0.00

voyage-4-lite is a lightweight, general-purpose embedding model optimized for low latency and cost. Enabled by Matryoshka learning and quantization-aware training, voyage-4-lite supports embeddings in 2048, 1024, 512, and 256 dimensions,…

コンテキスト

32K

入力

$0.02

出力

$0.00

voyage-code-4 is a code embedding model from Voyage AI, a MongoDB company. It is designed for coding agents and code retrieval, with Matryoshka embeddings at 2048, 1024, 512, and 256…

コンテキスト

32K

入力

$0.12

出力

$0.00

voyage-multimodal-3.5 is a state-of-the-art multimodal embedding model capable of vectorizing not only text, images, and video individually, but also content that interleaves all three modalities. It delivers excellent performance for…

コンテキスト

32K

入力

$0.12

出力

$0.00

Alibaba's most advanced video generation model, supporting over 10 visual creation capabilities in a unified system. Wan 2.6 generates 1080p video at 24fps from text, images, reference videos, or audio,…

コンテキスト

0

入力

$0.00

出力

$0.00

Wan 2.7 is a video generation model from Alibaba. It supports text-to-video, image-to-video with first and last frame control, and reference-to-video, where multiple reference images guide the style and content…

コンテキスト

0

入力

$0.00

出力

$0.00