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text-generation

automatic-speech-recognition

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text-generation

Llama-4-Scout-17B-16E-Instruct

meta-llama/Llama-4-Scout-17B-16E-Instruct cover image

The Llama 4 collection of models are natively multimodal AI models that enable text and multimodal experiences. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding. Llama 4 Scout, a 17 billion parameter model with 16 experts

$0.10 in, $0.30 out / 1M

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.

$0.18 / 1M tokens

text-generation

Muse-Glimmer-30B

meta-models/Muse-Glimmer-30B cover image

Muse Glimmer is a 30B multimodal agentic model distilled from Muse Spark — reasoning, tool use, and failure recovery in a single model that runs locally on consumer hardware.

$0.04 cached, $0.30 in, $1.20 out / 1M

text-generation

Mistral-Small-3.2-24B-Instruct-2506

mistralai/Mistral-Small-3.2-24B-Instruct-2506 cover image

Mistral-Small-3.2-24B-Instruct is a drop-in upgrade over the 3.1 release, with markedly better instruction following, roughly half the infinite-generation errors, and a more robust function-calling interface—while otherwise matching or slightly improving on all previous text and vision benchmarks.

$0.075 in, $0.20 out / 1M

Nemotron-3.5-Embed-1B-BF16

nvidia/Nemotron-3.5-Embed-1B-BF16 cover image

Nemotron-3.5-Embed-1B-BF16 is a compact multimodal embedding model from NVIDIA that maps text, images, and page screenshots into a shared 2048-dimensional vector space for visual document retrieval and semantic search. It pairs the Nemotron-3-Embed-1B text encoder with a vision encoder, supports up to 32k tokens and Matryoshka dimensions, and suits multilingual RAG over PDFs, slides, and scanned documents.

$0.015 / 1M tokens · $0.035 / 1M image tokens

Nemotron-3.5-Embed-8B-BF16

nvidia/Nemotron-3.5-Embed-8B-BF16 cover image

Nemotron-3.5-Embed-8B-BF16 is a multimodal embedding model from NVIDIA that maps text, images, and page screenshots into a shared 4096-dimensional vector space for visual document retrieval and semantic search. Built on the Nemotron-3-Embed-8B text encoder with a vision encoder, it supports up to 32k tokens and Matryoshka dimensions, and delivers the highest retrieval quality in the Nemotron 3.5 family.

$0.035 / 1M tokens · $0.070 / 1M image tokens

text-generation

Nemotron-Content-Safety-3.5

nvidia/Nemotron-Content-Safety-3.5 cover image

Nemotron Content Safety 3.5 is a multimodal safety classifier developed by NVIDIA. A compact safety model that handles text, images, and custom policies. It outputs a safe/unsafe classification plus a reasoning trace, and can be used as an inference-time guardrail, as a judge for LLM safety testing and evaluation, or with the accompanying training dataset to post-train models for safer behavior.

$0.20 / 1M tokens

text-generation

thinkingmachines/

thinkingmachines/Inkling-Small cover image

Inkling-Small is a Mixture-of-Experts transformer with 276B total parameters, 12B active, trained on NVIDIA GB300 NVL72 systems. Like Inkling, it features native reasoning over audio and images, variable thinking effort

$0.10 cached, $0.45 in, $1.20 out / 1M

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nvidia/Nemotron-3.5-Rerank-8B-BF16 Bria/fibo-2.0 nvidia/Nemotron-3.5-Embed-8B-BF16 nvidia/Nemotron-3.5-Embed-1B-BF16 deepseek-ai/DeepSeek-V4.1-Flash-1017

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