R1 Distill Llama 70B
VerifiedDeepSeek's distilled Llama 70B for advanced reasoning.
About R1 Distill Llama 70B
This model results from distilling DeepSeek R1 capabilities into the Llama 70B base architecture. The approach preserves core strengths while enabling broad accessibility through open weights. It operates exclusively in text modality without additional input types.
Its large context window supports extended documents and multi-turn interactions without losing coherence. Open-weight availability facilitates local deployment, fine-tuning, and integration into custom pipelines. The design emphasizes efficiency for text generation workloads.
Common uses include analytical tasks, content creation, and technical documentation support. Researchers apply it in academic settings while developers integrate it into applications needing reliable language models. The 70B scale balances performance with practical resource demands.
Capabilities
Benchmarks & performance
Independent evaluation scores and measured speed.
Source: Artificial Analysis
How R1 Distill Llama 70B compares
R1 Distill Llama 70B (striped bar) vs other language models on intelligence, speed and price.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · R1 Distill Llama 70B ranks #49 of 67
Speed
Output tokens per second · Higher is better · R1 Distill Llama 70B ranks #38 of 45
Price
USD per 1M output tokens · Lower is better · R1 Distill Llama 70B ranks #73 of 141
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long technical document analysis
The model processes and extracts insights from extensive technical texts within its 128000 token context window while maintaining coherence across large inputs.
Complex code generation projects
It generates, debugs, and refines substantial codebases by combining code generation with step-by-step reasoning and instruction following.
Advanced mathematical problem solving
Users apply it to multi-step math challenges that require detailed explanations and long-context reasoning for accurate solutions.
Strengths & limitations
Strengths
- +Efficient reasoning via distillation
- +Strong coding and math performance
- +Handles 128k token contexts
- +Text-only optimization
Limitations
- –Text modality only
- –Distilled model may lag full-scale versions
- –No built-in multimodal abilities
Cost calculator
Estimate what R1 Distill Llama 70B would cost for your usage.
Based on R1 Distill Llama 70B's $0.80/1M input · $0.80/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "deepseek/deepseek-r1-distill-llama-70b",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: deepseek/deepseek-r1-distill-llama-70b
Editor's verdict
R1 Distill Llama 70B is DeepSeek's open-weight language models with a 128K-token context window.
On independent testing it scores 16 on the Artificial Analysis Intelligence Index, running at roughly 49 tokens per second with about 0.61s to first token.
At $0.80 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to efficient reasoning via distillation and strong coding and math performance.
Frequently asked questions
The model handles a context window of 128000 tokens.
User reviews
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