โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Command R vs R1 Distill Llama 70B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Command R and R1 Distill Llama 70B.

Cohere

Command R

Command R is Cohere's lightweight, cost-efficient model engineered for high-speed enterprise integrations, productivity automation, and retrieval-augmented generation (RAG) pipelines. Optimized for low-latency API tool use and structured JSON output, it is particularly effective in enterprise search and question-answering systems where fast, reliable responses are critical. With a 128,000-token context window and a price of $0.15/MTok for input, Command R provides strong RAG performance and multilingual support at a fraction of the cost of Command R+, making it the preferred choice for teams scaling intelligent document retrieval at high request volumes.

View Full Specs
DeepSeek

R1 Distill Llama 70B

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...

View Full Specs

Technical Specifications

SpecificationCommand RR1 Distill Llama 70B
ProviderCohereDeepSeek
Context Window128,000 tokens128,000 tokens
Agent Suitability78/100N/A
Time to First Token (TTFT)200 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-03-112025-01-23

API Pricing Comparison

Input Price per Million Tokens

Command R

$0.15

R1 Distill Llama 70B

$0.80

Output Price per Million Tokens

Command R

$0.60

R1 Distill Llama 70B

$0.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
7100.0%vs8520.0%
Command R
R1 Distill Llama 70B
HumanEvalPython coding & logic synthesis
7300.0%vs8830.0%
Command R
R1 Distill Llama 70B
MATHComplex mathematical problem solving
5400.0%vs7000.0%
Command R
R1 Distill Llama 70B
GPQAGraduate-level expert reasoning
3500.0%vs4450.0%
Command R
R1 Distill Llama 70B
HellaSwagCommonsense reasoning and inference
7800.0%vs8600.0%
Command R
R1 Distill Llama 70B
MT-BenchMulti-turn conversation flow quality
750.0%vs905.0%
Command R
R1 Distill Llama 70B

Command R Quirks & Gotchas

  • โ–ธCost-effective RAG model โ€” strong multilingual search performance
  • โ–ธLimited agentic capability โ€” use Command R+ for complex multi-step tool use

R1 Distill Llama 70B Quirks & Gotchas

No developer gotchas reported.