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ERNIE 4.5 VL 424B A47B vs Gemini 3.1 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 ERNIE 4.5 VL 424B A47B and Gemini 3.1 Flash.

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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Google

Gemini 3.1 Flash

Gemini 3.1 Flash is Google's high-speed, cost-efficient multimodal model in the 3.1 generation, purpose-built for high-volume content synthesis, classification, and intelligent routing at scale. Featuring a 1-million-token context window, it can process large batches of documents, customer data, or multimedia content in a single inference pass, dramatically reducing pipeline complexity. At just $0.25/MTok for input, it is one of the most affordable routes to Google-caliber multimodal AI, making it an ideal backbone for production pipelines, data enrichment workflows, and high-frequency API integrations.

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Technical Specifications

SpecificationERNIE 4.5 VL 424B A47BGemini 3.1 Flash
ProviderBaiduGoogle
Context Window131,072 tokens1,000,000 tokens
Agent SuitabilityN/A86/100
Time to First Token (TTFT)N/A150 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-06-302026-04-20

API Pricing Comparison

Input Price per Million Tokens

ERNIE 4.5 VL 424B A47B

$0.42

Gemini 3.1 Flash

$0.25

Output Price per Million Tokens

ERNIE 4.5 VL 424B A47B

$1.25

Gemini 3.1 Flash

$1.50

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
8680.0%vs8680.0%
ERNIE 4.5 VL 424B A47B
Gemini 3.1 Flash
HumanEvalPython coding & logic synthesis
8200.0%vs8850.0%
ERNIE 4.5 VL 424B A47B
Gemini 3.1 Flash
MATHComplex mathematical problem solving
6520.0%vs7820.0%
ERNIE 4.5 VL 424B A47B
Gemini 3.1 Flash
GPQAGraduate-level expert reasoning
4500.0%vs6050.0%
ERNIE 4.5 VL 424B A47B
Gemini 3.1 Flash
HellaSwagCommonsense reasoning and inference
8650.0%vs9520.0%
ERNIE 4.5 VL 424B A47B
Gemini 3.1 Flash
MT-BenchMulti-turn conversation flow quality
895.0%vs900.0%
ERNIE 4.5 VL 424B A47B
Gemini 3.1 Flash

ERNIE 4.5 VL 424B A47B Quirks & Gotchas

No developer gotchas reported.

Gemini 3.1 Flash Quirks & Gotchas

  • Most cost-effective Google model — ideal for high-volume pipelines
  • Context caching available via Vertex AI for repeated document processing