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

Command R vs DeepSeek V4 Flash

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 DeepSeek V4 Flash.

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

DeepSeek V4 Flash

DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...

View Full Specs

Technical Specifications

SpecificationCommand RDeepSeek V4 Flash
ProviderCohereDeepSeek
Context Window128,000 tokens1,048,576 tokens
Agent Suitability78/10086/100
Time to First Token (TTFT)200 ms120 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-03-112026-04-24

API Pricing Comparison

Input Price per Million Tokens

Command R

$0.15

DeepSeek V4 Flash

$0.09

Output Price per Million Tokens

Command R

$0.60

DeepSeek V4 Flash

$0.18

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%vs8240.0%
Command R
DeepSeek V4 Flash
HumanEvalPython coding & logic synthesis
7300.0%vs8410.0%
Command R
DeepSeek V4 Flash
MATHComplex mathematical problem solving
5400.0%vs5020.0%
Command R
DeepSeek V4 Flash
GPQAGraduate-level expert reasoning
3500.0%vs3800.0%
Command R
DeepSeek V4 Flash
HellaSwagCommonsense reasoning and inference
7800.0%vs8350.0%
Command R
DeepSeek V4 Flash
MT-BenchMulti-turn conversation flow quality
750.0%vs875.0%
Command R
DeepSeek V4 Flash

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

DeepSeek V4 Flash Quirks & Gotchas

  • โ–ธBest cost-per-token ratio of any hosted API โ€” ideal for high-throughput pipelines
  • โ–ธLower agentic performance vs V4 Pro โ€” route complex tool calls accordingly