Comprehensive side-by-side LLM comparison
DeepSeek-R1 offers 6.1K more tokens in context window than Llama 3.2 90B Instruct. Llama 3.2 90B Instruct is $1.99 cheaper per million tokens. Llama 3.2 90B Instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-R1 was developed as a reasoning-focused language model, designed to combine chain-of-thought reasoning with reinforcement learning techniques. Built to excel at complex problem-solving through trial-and-error learning and deliberate analytical processes, it demonstrates the power of efficient training methods in open-source model development.
Meta
Llama 3.2 90B was developed as a flagship-tier open-source model, designed to provide advanced capabilities with 90 billion parameters. Built to serve applications requiring high-quality reasoning and generation, it represents a powerful option within the Llama 3.2 series for demanding tasks.
3 months newer

Llama 3.2 90B Instruct
Meta
2024-09-25

DeepSeek-R1
DeepSeek
2025-01-20
Cost per million tokens (USD)

DeepSeek-R1

Llama 3.2 90B Instruct
Context window and performance specifications
Available providers and their performance metrics

DeepSeek-R1
DeepInfra
DeepSeek
Fireworks
Together
ZeroEval

DeepSeek-R1

Llama 3.2 90B Instruct

DeepSeek-R1

Llama 3.2 90B Instruct

Llama 3.2 90B Instruct
Bedrock
DeepInfra
Fireworks
Hyperbolic
Together