AI Tools Review

DeepSeek: R1 Distill Llama 70B

By Deepseek

Released: 2025-01-23

API
LLM
RAG
Deepseek
Paid
New

Deepseek Deepseek R1 Distill Llama 70B, developed by DeepSeek, features 70B parameters and 131k-token context window. DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across multiple benchmarks, including: - AIME 2024 pass@1: 70.0 - MATH-500 pass@1: 94.5 - CodeForces Rating: 1633 The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models. Priced affordably at $0.03/1M tokens.

Visit DeepSeek: R1 Distill Llama 70B

AI-Powered

Leverages advanced AI technology to deliver cutting-edge capabilities and results.

Fast & Efficient

Optimized performance ensures quick results without compromising on quality.

Purpose-Built

Specifically designed for llms tasks and workflows.

Deepseek Model Timeline

DeepSeek: DeepSeek V3.2 Speciale

164k tokens context

DeepSeek: DeepSeek V3.2

164k tokens context

DeepSeek: DeepSeek V3.2 Exp

164k tokens context

DeepSeek: DeepSeek V3.1 Terminus (exacto)

164k tokens context

DeepSeek: DeepSeek V3.1 Terminus

164k tokens context

DeepSeek: DeepSeek V3.1

33k tokens context

DeepSeek: R1 0528 (free)

164k tokens context

DeepSeek: R1 0528

164k tokens context

DeepSeek: DeepSeek V3 0324

164k tokens context

DeepSeek: R1 Distill Qwen 32B

33k tokens context

DeepSeek: R1 Distill Llama 70BCurrent

131k tokens context

DeepSeek: R1

64k tokens context

DeepSeek: DeepSeek V3

164k tokens context

Specifications

pricing$0.03 / $0.11 (per 1M)
context Window131k tokens

AI Evaluation

4.8
Expert Rating
Text4.9/5
Coding3.5/5

Specialized for mathematical reasoning and quantitative problem-solving. Handles complex equations, proofs, and numerical analysis with precision.

Pros

  • Budget-friendly at $0.03/1M tokens
  • 131k token context window
  • Large-scale 70B architecture
  • Mathematical reasoning

Cons

  • API integration required
  • May need prompt tuning