What it's for
- Local reasoning: running a reasoning model on my own machine without sending my data to OpenAI.
- Math and logic: R1's reasoning chains hold up well for solving multi-step problems.
- A base for fine-tuning: the community starts from R1 to build specialized models (legal, medical, and so on).
- Learning how a model reasons: R1 shows its reasoning step by step, which makes it a great teaching tool.
- A historical archive: to understand how open source caught up with OpenAI in 2025.
How it compares
vs DeepSeek V3.2: V3.2 is the current all-rounder, more versatile. R1 is still better at pure reasoning, but V3.2 has a "thinking" mode that gets close. Pick R1 if all you want is reasoning, V3.2 otherwise.
vs OpenAI o1 / o3: o1/o3 are closed, R1 is open. Performance was close in January 2025; OpenAI has pulled slightly ahead since, but R1 still holds up for plenty of uses.
vs Llama 4 Behemoth: Behemoth is stronger at reasoning, but far heavier (impossible to run locally on a consumer machine). R1 is more accessible.
What it costs
Prices as of May 25, 2026:
- Model weights: free on huggingface.co/deepseek-ai
- License: MIT (free, usable commercially)
- Official DeepSeek API: ~$0.55 / million tokens (input) — pricier than V3.2 because reasoning burns more
- Via Fireworks or Together: $1-3 / million tokens depending on the provider
My take
I don't use R1 directly anymore — V3.2 is better for most of my cases and costs less. But R1 is still the founding moment of 2025, the one that proved open source can produce cutting-edge models.
If you're just getting into AI in 2026, you don't need to use R1. If you do research, or you want to understand how open-source AI exploded, it's a reference worth knowing.
Its real value today: the base that dozens of community models were built on.
Quick questions
Is DeepSeek R1 outdated?
DeepSeek R1 is the open-weight reasoning model released by DeepSeek in January 2025, under an MIT license. The first o1-style reasoning with free weights, it marked the moment open source caught up.
Can I run it on my MacBook?
Not the full R1 (671 billion parameters). But distilled versions (7B, 32B) run on a MacBook M3/M4.
Is R1 free for commercial use?
Yes, MIT license, usable with no restrictions.
Checked on 2026-05-25 · next review 2026-11-25
Specs and prices checked on Hugging Face and the official DeepSeek docs. Page documented as an archive and to help you understand the open-weight ecosystem.