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All categories and models you can try out and directly use in deepinfra:

text-generation

automatic-speech-recognition

zero-shot-image-classification

text-generation

gemini-2.0-flash-001

google/gemini-2.0-flash-001 cover image

976k

$0.10 in, $0.40 out / 1M

text-to-video

google/veo-3.0 cover image

Veo 3 is a state-of-the-art text-to-video model from Google that generates high-fidelity, cinematic videos with synchronized audio from a simple text prompt. It excels at creating realistic and imaginative scenes with a deep understanding of natural language and visual dynamics.

$0.4 / second

text-to-video

google/veo-3.0-fast cover image

Veo 3 Fast is a speed-optimized version of the Veo 3 model, designed for rapid video creation. While maintaining high quality, it delivers results in a fraction of the time, making it ideal for quick iterations and dynamic content generation.

$0.15 / second

embeddings

intfloat/e5-base-v2 cover image

Text Embeddings by Weakly-Supervised Contrastive Pre-training. Model has 24 layers and 1024 out dim.

512

$0.005 / 1M tokens

embeddings

intfloat/e5-large-v2 cover image

Text Embeddings by Weakly-Supervised Contrastive Pre-training. Model has 24 layers and 1024 out dim.

512

$0.010 / 1M tokens

embeddings

multilingual-e5-large

intfloat/multilingual-e5-large cover image

The Multilingual-E5-large model is a 24-layer text embedding model with an embedding size of 1024, trained on a mixture of multilingual datasets and supporting 100 languages.

fp32

512

$0.010 / 1M tokens

embeddings

multilingual-e5-large-instruct

intfloat/multilingual-e5-large-instruct cover image

The Multilingual-E5 models, initialized from XLM-RoBERTa, support up to 512 tokens per input — any longer text will be silently truncated. To ensure optimal performance, always prefix inputs with “query:” or “passage:”, as the model was explicitly trained with this format.

512

$0.0005 / second

text-generation

Llama-3.2-11B-Vision-Instruct

meta-llama/Llama-3.2-11B-Vision-Instruct cover image

Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis. Its ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research.

fp8

128k

$0.049 / 1M tokens

text-generation

Llama-3.2-3B-Instruct

meta-llama/Llama-3.2-3B-Instruct cover image

The Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out)

bfloat16

128k

$0.02 / 1M tokens

text-generation

Llama-Guard-3-8B

meta-llama/Llama-Guard-3-8B cover image

Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM – it generates text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated.

bfloat16

128k

Deprecated

text-generation

Llama-Guard-4-12B

meta-llama/Llama-Guard-4-12B cover image

Llama Guard 4 is a natively multimodal safety classifier with 12 billion parameters trained jointly on text and multiple images. Llama Guard 4 is a dense architecture pruned from the Llama 4 Scout pre-trained model and fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It itself acts as an LLM: it generates text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated.

bfloat16

160k

Deprecated

text-generation

Meta-Llama-3-8B-Instruct

meta-llama/Meta-Llama-3-8B-Instruct cover image

Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes.

bfloat16

8k

$0.03 in, $0.06 out / 1M

text-generation

Meta-Llama-3.1-70B-Instruct

meta-llama/Meta-Llama-3.1-70B-Instruct cover image

Meta developed and released the Meta Llama 3.1 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8B, 70B and 405B sizes

bfloat16

128k

$0.40 / 1M tokens

text-generation

Meta-Llama-3.1-70B-Instruct-Turbo

meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo cover image

Meta developed and released the Meta Llama 3.1 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8B, 70B and 405B sizes

fp8

128k

$0.40 / 1M tokens

text-generation

Meta-Llama-3.1-8B-Instruct

meta-llama/Meta-Llama-3.1-8B-Instruct cover image

Meta developed and released the Meta Llama 3.1 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8B, 70B and 405B sizes

bfloat16

128k

$0.03 in, $0.05 out / 1M

text-generation

Meta-Llama-3.1-8B-Instruct-Turbo

meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo cover image

Meta developed and released the Meta Llama 3.1 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8B, 70B and 405B sizes

fp8

128k

$0.02 in, $0.03 out / 1M

text-generation

WizardLM-2-8x22B

microsoft/WizardLM-2-8x22B cover image

WizardLM-2 8x22B is Microsoft AI's most advanced Wizard model. It demonstrates highly competitive performance compared to those leading proprietary models.

bfloat16

64k

$0.48 / 1M tokens

text-generation

Mistral-Nemo-Instruct-2407

mistralai/Mistral-Nemo-Instruct-2407 cover image

12B model trained jointly by Mistral AI and NVIDIA, it significantly outperforms existing models smaller or similar in size.

fp8

128k

$0.02 in, $0.04 out / 1M

text-generation

Mistral-Small-24B-Instruct-2501

mistralai/Mistral-Small-24B-Instruct-2501 cover image

Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed for efficient local deployment. The model achieves 81% accuracy on the MMLU benchmark and performs competitively with larger models like Llama 3.3 70B and Qwen 32B, while operating at three times the speed on equivalent hardware.

fp8

32k

$0.05 in, $0.08 out / 1M

text-generation

Mixtral-8x7B-Instruct-v0.1

mistralai/Mixtral-8x7B-Instruct-v0.1 cover image

Mixtral is mixture of expert large language model (LLM) from Mistral AI. This is state of the art machine learning model using a mixture 8 of experts (MoE) 7b models. During inference 2 expers are selected. This architecture allows large models to be fast and cheap at inference. The Mixtral-8x7B outperforms Llama 2 70B on most benchmarks.

fp8

32k

$0.54 / 1M tokens

text-generation

Llama-3.1-Nemotron-70B-Instruct

nvidia/Llama-3.1-Nemotron-70B-Instruct cover image

Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries. This model reaches Arena Hard of 85.0, AlpacaEval 2 LC of 57.6 and GPT-4-Turbo MT-Bench of 8.98, which are known to be predictive of LMSys Chatbot Arena Elo. As of 16th Oct 2024, this model is #1 on all three automatic alignment benchmarks (verified tab for AlpacaEval 2 LC), edging out strong frontier models such as GPT-4o and Claude 3.5 Sonnet.

fp8

128k

$0.60 / 1M tokens

text-generation

Llama-3.3-Nemotron-Super-49B-v1.5

nvidia/Llama-3.3-Nemotron-Super-49B-v1.5 cover image

Llama-3.3-Nemotron-Super-49B-v1.5 is a large language model (LLM) optimized for advanced reasoning, conversational interactions, retrieval-augmented generation (RAG), and tool-calling tasks. Derived from Meta's Llama-3.3-70B-Instruct, it employs a Neural Architecture Search (NAS) approach, significantly enhancing efficiency and reducing memory requirements.

fp8

128k

$0.10 in, $0.40 out / 1M

text-generation

NVIDIA-Nemotron-Nano-9B-v2

nvidia/NVIDIA-Nemotron-Nano-9B-v2 cover image

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.

bfloat16

128k

$0.04 in, $0.16 out / 1M

image-classification

clip-vit-base-patch32

openai/clip-vit-base-patch32 cover image

The CLIP model was developed by OpenAI to investigate the robustness of computer vision models. It uses a Vision Transformer architecture and was trained on a large dataset of image-caption pairs. The model shows promise in various computer vision tasks but also has limitations, including difficulties with fine-grained classification and potential biases in certain applications.

$0.0005 / second

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