DeepSeek: R1 Distill Llama 70B
DeepSeek: R1 Distill Llama 70B is for people who want reasoning-heavy output without paying premium rates. It sits firmly in the cheap tier at $0.70 input and $0.80 output per 1M tokens, and the real-world costs are tiny: about $0.06 for 100 short chats, $0.06 for a long PDF with questions, and $0.46 for 1,000 coding completions. The non-obvious upside is that this price point makes it practical for workflows where you want the model to think a bit more often instead of rationing every call.
Best for
- •Cheap reasoning tasks where you need solid answers at scale without watching every token.
- •Structured output jobs like extraction, classification, and JSON-shaped responses.
- •Long-context document Q&A when you need to feed in large PDFs and keep costs low.
Not ideal for
- •Use cases where you specifically need vision or multimodal input.
- •Teams that only buy models through bundled chat subscriptions, since none are listed in our catalog.
What it costs in real life
Computed from OpenRouter API pricing ($0.70 input / $0.80 output per 1M tokens)
Frequently Asked Questions
Is DeepSeek: R1 Distill Llama 70B worth it for everyday API use?
Yes, if your work is mostly text reasoning, coding help, extraction, or document Q&A. The pricing is unusually low for that kind of usage, so you can run frequent calls without turning a simple workflow into a budget problem.
How much does DeepSeek: R1 Distill Llama 70B actually cost in practice?
The raw API price is $0.70 per 1M input tokens and $0.80 per 1M output tokens. In real usage, that comes out to about $0.06 for 100 short chats, $0.06 for one long PDF plus questions, and $0.46 for 1,000 coding completions.
Should I use DeepSeek: R1 Distill Llama 70B for coding or agents?
Yes, especially when you care about keeping repeated calls cheap. A 50-step agent workflow is only about $0.06, which makes experimentation much less painful than with higher-priced reasoning models.
Capabilities
Cheapest access path
The cheapest way to use it is direct API usage at $0.70 per 1M input tokens and $0.80 per 1M output tokens. That keeps common workloads very cheap, including roughly $0.06 for a 50-step agent workflow; StackTrim AI is useful here because we found no subscription in our catalog that already includes this model.