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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+

Cohere's enterprise-optimized model built for advanced Retrieval-Augmented Generation (RAG) and multi-step tool use. Highly effective for multilingual business processes.

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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...

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Technical Specifications

SpecificationCommand R+R1 Distill Llama 70B
ProviderCohereDeepSeek
Context Window128,000 tokens128,000 tokens
Agent Suitability86/100N/A
Time to First Token (TTFT)350 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-04-042025-01-23

API Pricing Comparison

Input Price per Million Tokens

Command R+

$2.50

R1 Distill Llama 70B

$0.80

Output Price per Million Tokens

Command R+

$10.00

R1 Distill Llama 70B

$0.80

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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
7570.0%vs8520.0%
Command R+
R1 Distill Llama 70B
HumanEvalPython coding & logic synthesis
7800.0%vs8830.0%
Command R+
R1 Distill Llama 70B
MATHComplex mathematical problem solving
6200.0%vs7000.0%
Command R+
R1 Distill Llama 70B
GPQAGraduate-level expert reasoning
4200.0%vs4450.0%
Command R+
R1 Distill Llama 70B
HellaSwagCommonsense reasoning and inference
8250.0%vs8600.0%
Command R+
R1 Distill Llama 70B
MT-BenchMulti-turn conversation flow quality
800.0%vs905.0%
Command R+
R1 Distill Llama 70B

Command R+ Quirks & Gotchas

  • โ–ธOptimized for RAG workflows โ€” best enterprise document search model
  • โ–ธTool calling requires explicit step definitions in Cohere's tool-use format

R1 Distill Llama 70B Quirks & Gotchas

No developer gotchas reported.