Listed together in guide “Open-source AI models”
Google's family of lightweight open-weight models derived from the same research as Gemini, currently in the Gemma 4 generation.
Open (open weights/source) Gemma Terms of Use
Use cases
- Running capable models locally on consumer hardware
- On-device and edge AI applications
- Fine-tuning small models for focused tasks
Pricing: Gemma weights are free to download under the Gemma license; hosted inference is available through Google and third parties at usage prices.
Sources
This record was last reviewed on 2026-09-10.
Listed together in guide “Open-source AI models”
Family of small open-weight language models from Microsoft, designed for strong reasoning at compact sizes.
Open (open weights/source) MIT
Use cases
- Running capable models on laptops and phones
- Cost-efficient inference for simple tasks
- Research on synthetic-data training
Pricing: Phi models are free under the MIT license; hosted inference through Azure AI Foundry is billed by usage.
Sources
This record was last reviewed on 2026-10-09.
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German AI company that builds sovereign large language models and enterprise AI platforms for industry, public-sector, and defense customers.
Paid
Use cases
- Public-sector and defense applications that require data to stay in Europe
- Enterprise assistants in industry, administration, and science
- Research collaborations on transparent language models
Pricing: Aleph Alpha sells to organizations rather than consumers and does not publish list prices; commercial terms are arranged directly with enterprise and public-sector customers.
Documentation ↗ · Sources
This record was last reviewed on 2026-09-10.
Related: shares the task Running models yourself
Managed AWS service for building applications with foundation models from multiple providers via one API.
Paid
Use cases
- Enterprise apps that need a choice of models under one API
- RAG systems grounded in private company data
- Regulated workloads requiring AWS data controls
Pricing: Pricing is usage-based per input/output token, with on-demand and provisioned-throughput options.
Pricing ↗ · Documentation ↗ · Sources
This record was last reviewed on 2026-10-09.
Related: shares the task Running models yourself
AWS portfolio of Amazon-built foundation models and services for text, multimodal, speech, custom model building, and UI-automating agents.
Paid
Use cases
- Cost-sensitive chat, summarization, and multimodal analysis on AWS
- Building a custom frontier model with Nova Forge
- Automating production UI workflows with Nova Act agents
Pricing: Amazon Nova is billed through AWS, typically via Amazon Bedrock, with usage-based pricing that varies by model and service.
Pricing ↗ · Documentation ↗ · Sources
This record was last reviewed on 2026-09-04.
Related: shares the task Running models yourself
Open-weight bilingual LLM family from Beijing-based Baichuan Intelligence, now focused on medical AI with its Baichuan-M reasoning models.
Open (open weights/source) Baichuan Community License
Use cases
- Building Chinese-language NLP applications on open weights
- Research on bilingual large language models
- Medical AI assistants based on the Baichuan-M series
Pricing: Open-weight Baichuan models are free to download for research, with licensing terms for commercial use; hosted APIs are billed by usage.
Sources
This record was last reviewed on 2026-09-10.
Related: shares the task Running models yourself
Platform for deploying and serving machine-learning models as scalable APIs.
Paid
Use cases
- Serving custom and open models in production
- Low-latency inference APIs
- Scaling ML services reliably
Pricing: Dedicated GPU compute is billed per minute with no charge for idle time, model APIs are billed per million tokens, and new accounts come with credits.
Documentation ↗ · Sources
This record was last reviewed on 2026-10-09.
Related: shares the task Running models yourself
Python serving framework for packaging AI models and custom inference pipelines into deployable services.
Open (open weights/source)
Use cases
- Serving AI models to applications
- Deployment of production inference endpoints
Pricing: Self-hosting the open-source project and buying the hosted platform are separate choices. The hosted service has its own plans and usage limits; self-hosting still requires infrastructure and any model-provider charges.
Documentation ↗ · Sources
This record was last reviewed on 2026-11-03.