Forefront

What it does

Forefront is a developer platform for importing, fine-tuning, evaluating, and serving open-source text-generation models. Developers can supply JSONL datasets containing example inputs and outputs, or store model outputs in pipelines for later fine-tuning. They can test models in a Playground, inspect datasets, review validation results and training-loss charts, and run evaluations. The platform exposes chat and completion APIs; outputs are generated text. Models can be imported from Hugging Face or exported for self-hosting or hosting with another provider.

The product is aimed at developers and teams building with open-source AI, including research, startup, and enterprise users. Access is documented through a web Playground and API; API use requires a Forefront API key, and the examples use Forefront's Python or JavaScript libraries. The pricing page lists a free plan, a Team plan, and custom-priced Enterprise service, with inference and fine-tuning charges measured per 1,000 tokens. The documentation states that prompt and generated-output tokens share a model-specific context-length limit. It does not establish which models are currently available or detail the conditions attached to the included free credits.

What it can do

• Fine-tune open-source text-generation models on JSONL datasets
• Import models from Hugging Face
• Evaluate models and review validation results
• Inspect dataset samples and token distributions
• Serve models through chat and completion APIs
• Store model outputs in pipelines and export fine-tuned models

Works with

• Hugging Face

Before you choose

• Fine-tuning and inference have separate per-token charges; pricing lists $0.008 per 1,000 tokens for Mistral-7B fine-tuning and $0.001 per 1,000 tokens for inference.
• The pricing page says every plan includes $20 in free credits, but does not specify their expiry or other redemption conditions.
• Prompt and generated-output tokens combined must remain within each model's context limit; the available models and their limits may vary.

Listed under

• Coding
• AI-data-pipelines
• Developers
• Fine-tuning
• LLM-API
• Model-evaluation
• Open-source-models

Get started

1. Create an account using the official site's free-start option.
2. Choose or import an open-source model and prepare JSONL examples for fine-tuning.
3. Use the Playground to test the model, or obtain an API key to call chat or completion endpoints.

Every plan includes $20 in free credits for fine-tuning and inference. Listed Mistral-7B usage: inference $0.001 per 1,000 tokens; fine-tuning $0.008 per 1,000 tokens. Credit expiry and other conditions are not stated. The $20 credit is not established as recurring. Free subscription access does not make compute unlimited or free after credits. Confirm current models and dollar currency.

Source: forefront.ai/pricing, checked 2 Nov 2026. Prices can change; check before you buy.

Sources for this overview

Product pages, documentation, and pricing checked 2 Nov 2026. Each source supports part of the overview; availability and prices can change.

• Introduction | Forefront ↗docs.forefront.ai
• Forefront ↗forefront.ai
• Forefront ↗forefront.ai
• ForeFront Solutions – World Class WordPress Development Agency ↗forefront.dev
• Forefront ↗forefront.ai

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forefront.ai: product, pricing and policy pages

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Last checked 2 Nov 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.