cd/sources/dev-to· home sources Dev.to
cat /sources/dev-to.feed | wc -l → 9452

Dev.to

articles 9452 domain dev.to → page 251/473 feed RSS
20:21
2026-06-16
dev.to
artificial-intelligence

Notion AI's Pricing Trap: Why I Went Open Source Instead

A developer abandoned Notion AI after its pricing ballooned, opting for open-source alternatives. Benchmarking showed Notion AI's optimized 2026 stack offered 40-65% cost reduction but relied on commu…

20:20
2026-06-16
dev.to
large-language-models

How to Give ChatGPT Web Scraping with MCP Connectors (2026)

A developer built a bridge to connect ChatGPT's custom MCP connectors with the local web scraping tool CrawlForge, since ChatGPT requires remote servers. The solution uses a thin FastMCP wrapper that …

19:37
2026-06-16
dev.to
large-language-models

Serving any LLM using a single command line with Flama

Flama 2.0 introduces first-class support for generative AI, enabling users to download, package, and serve large language models (LLMs) via a single command line. The framework allows fetching models …

19:36
2026-06-16
dev.to
large-language-models

Best LLM Models for Conversational AI in Language Learning

Oxlo.ai's request-based pricing enables developers to build a conversational language tutor that corrects mistakes in real time and adapts to learner proficiency. Using the llama-3.3-70b model via the…

19:35
2026-06-16
dev.to
artificial-intelligence

Airtable AI From Scratch: A Freelance Dev's Cost Breakdown

A freelance developer rebuilt their AI stack around Airtable AI, reducing monthly API costs from $89 to $14—an 84% drop—by switching from GPT-4o to cheaper models like DeepSeek V4 Flash and Qwen3-32B …

19:35
2026-06-16
dev.to
natural-language-processing

Unlocking Efficient Named Entity Recognition with Oxlo.ai

Oxlo.ai offers request-based pricing for LLM-driven named entity recognition, making it economically viable for long documents. The platform supports structured output via JSON mode and function calli…

19:35
2026-06-16
dev.to
large-language-models

Overcoming LLM Limitations

A developer shipped a small research agent that addresses three common LLM limitations: stale training data, hallucinated facts, and arithmetic errors. The agent uses tool calling to look up facts and…

19:34
2026-06-16
dev.to
large-language-models

Advantages and Disadvantages of Using LLM

A developer built a Python CLI tool that uses Oxlo.ai's LLM to evaluate whether a business task is suitable for automation with a large language model. The tool sends a task description to the llama-3…

19:31
2026-06-16
dev.to
large-language-models

Reducing LLM Costs: Best Practices and Techniques

Oxlo.ai offers flat per-request pricing for LLM APIs, decoupling cost from context size and enabling long-context applications without token-based billing. The company provides techniques such as prom…

19:31
2026-06-16
dev.to
large-language-models

The Future of Large Language Models

Oxlo.ai is building an autonomous research agent that converts vague questions into structured plans, gathers evidence across multiple LLM calls, and synthesizes markdown reports. The agent uses small…

19:26
2026-06-16
dev.to
large-language-models

LLM Trends and Future Outlook

Oxlo.ai has introduced a request-based pricing model and an OpenAI-compatible API supporting over 45 models across seven categories, addressing the cost unpredictability of token-based billing for lon…

19:24
2026-06-16
dev.to
ai-products

LLM Pricing Models: Flat Rate vs Token-Based

Oxlo.ai offers request-based pricing for AI inference, charging a flat fee per API call regardless of prompt length, contrasting with token-based models used by providers like Together AI and Firework…

19:24
2026-06-16
dev.to
large-language-models

Comparing LLM Inference APIs: Cost, Performance, and More

A developer compared LLM inference APIs on cost, performance, and integration, noting that most providers use token-based pricing which can cause unpredictable costs for long-context or agentic worklo…

← prev page 251 / 473 next →