GPT-4o performance at ~5% of the cost. The most disruptive open-source LLM of 2026.
DeepSeek-V3 is a 671B-parameter mixture-of-experts model from Chinese AI lab DeepSeek. Despite having 37B active parameters per token, it matches GPT-4o and Claude 3.5 Sonnet on most reasoning, coding, and math benchmarks — and costs ~95% less via API. The model is fully open-source under MIT license, meaning you can self-host, fine-tune, or distill it for commercial use without restriction.
Who it's for: Developers shipping LLM features, startups watching their OpenAI bill, enterprises needing on-prem deployment, researchers benchmarking open models.
671B total parameters but only 37B active per forward pass — gives GPT-4-class quality at Llama-3-70B inference cost. Trained on 14.8T tokens.
128K token context window via YaRN scaling. Handles full codebases, long legal documents, and entire books in one prompt.
Weights, code, and training data documentation all released under MIT license. Self-host, fine-tune commercially, distill — no restrictions.
API pricing: $0.14/M input, $0.28/M output. Compare: GPT-4o ($2.50/$10), Claude 3.5 Sonnet ($3/$15). 95%+ savings at scale.
DeepSeek-R1-Distill versions fine-tuned into Llama 3.1 8B/70B and Qwen 2.5 1.5B/7B/14B/32B — runs on consumer GPUs.
DeepSeek-V3 is the most important open-source LLM release since Llama 2. If you're building an LLM-powered product and you're not using it yet, you're likely overpaying 10-20x for OpenAI. The API is a no-brainer for cost-sensitive startups. Self-hosting requires serious hardware but gives you total control. Just be aware of the geopolitical reality and test for your use case.
Free chat interface for DeepSeek-V3 and R1. No signup needed.
Reasoning model matching o1 on math and coding benchmarks.
OpenAI's generalist assistant. Best ecosystem and plugins.
Anthropic's assistant. Best long-form writing and code review.