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Command R vs ERNIE 4.5 VL 424B A47B

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 ERNIE 4.5 VL 424B A47B.

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.

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Baidu

ERNIE 4.5 VL 424B A47B

ERNIE-4.5-VL-424B-A47B is a multimodal Mixture-of-Experts (MoE) model from Baidu’s ERNIE 4.5 series, featuring 424B total parameters with 47B active per token. It is trained jointly on text and image data...

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Technical Specifications

SpecificationCommand RERNIE 4.5 VL 424B A47B
ProviderCohereBaidu
Context Window128,000 tokens131,072 tokens
Agent Suitability78/100N/A
Time to First Token (TTFT)200 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-03-112025-06-30

API Pricing Comparison

Input Price per Million Tokens

Command R

$0.15

ERNIE 4.5 VL 424B A47B

$0.42

Output Price per Million Tokens

Command R

$0.60

ERNIE 4.5 VL 424B A47B

$1.25

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%vs8680.0%
Command R
ERNIE 4.5 VL 424B A47B
HumanEvalPython coding & logic synthesis
7300.0%vs8200.0%
Command R
ERNIE 4.5 VL 424B A47B
MATHComplex mathematical problem solving
5400.0%vs6520.0%
Command R
ERNIE 4.5 VL 424B A47B
GPQAGraduate-level expert reasoning
3500.0%vs4500.0%
Command R
ERNIE 4.5 VL 424B A47B
HellaSwagCommonsense reasoning and inference
7800.0%vs8650.0%
Command R
ERNIE 4.5 VL 424B A47B
MT-BenchMulti-turn conversation flow quality
750.0%vs895.0%
Command R
ERNIE 4.5 VL 424B A47B

Command R Quirks & Gotchas

  • Cost-effective RAG model — strong multilingual search performance
  • Limited agentic capability — use Command R+ for complex multi-step tool use

ERNIE 4.5 VL 424B A47B Quirks & Gotchas

No developer gotchas reported.