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

Command R vs Step 3.7 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 Step 3.7 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
StepFun

Step 3.7 Flash

Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters...

View Full Specs

Technical Specifications

SpecificationCommand RStep 3.7 Flash
ProviderCohereStepFun
Context Window128,000 tokens256,000 tokens
Agent Suitability78/100N/A
Time to First Token (TTFT)200 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-03-112026-05-28

API Pricing Comparison

Input Price per Million Tokens

Command R

$0.15

Step 3.7 Flash

$0.20

Output Price per Million Tokens

Command R

$0.60

Step 3.7 Flash

$1.15

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%vs8450.0%
Command R
Step 3.7 Flash
HumanEvalPython coding & logic synthesis
7300.0%vs8600.0%
Command R
Step 3.7 Flash
MATHComplex mathematical problem solving
5400.0%vs6680.0%
Command R
Step 3.7 Flash
GPQAGraduate-level expert reasoning
3500.0%vs4400.0%
Command R
Step 3.7 Flash
HellaSwagCommonsense reasoning and inference
7800.0%vs8580.0%
Command R
Step 3.7 Flash
MT-BenchMulti-turn conversation flow quality
750.0%vs890.0%
Command R
Step 3.7 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

Step 3.7 Flash Quirks & Gotchas

No developer gotchas reported.