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

Gemini 3.1 Flash vs GPT-4o-mini

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 Gemini 3.1 Flash and GPT-4o-mini.

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.

View Full Specs
OpenAI

GPT-4o-mini

GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...

View Full Specs

Technical Specifications

SpecificationGemini 3.1 FlashGPT-4o-mini
ProviderGoogleOpenAI
Context Window1,000,000 tokens128,000 tokens
Agent Suitability86/10082/100
Time to First Token (TTFT)150 ms150 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202024-07-18

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Flash

$0.25

GPT-4o-mini

$0.15

Output Price per Million Tokens

Gemini 3.1 Flash

$1.50

GPT-4o-mini

$0.60

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%vs8200.0%
Gemini 3.1 Flash
GPT-4o-mini
HumanEvalPython coding & logic synthesis
8850.0%vs8400.0%
Gemini 3.1 Flash
GPT-4o-mini
MATHComplex mathematical problem solving
7820.0%vs7020.0%
Gemini 3.1 Flash
GPT-4o-mini
GPQAGraduate-level expert reasoning
6050.0%vs4500.0%
Gemini 3.1 Flash
GPT-4o-mini
HellaSwagCommonsense reasoning and inference
9520.0%vs8470.0%
Gemini 3.1 Flash
GPT-4o-mini
MT-BenchMulti-turn conversation flow quality
900.0%vs860.0%
Gemini 3.1 Flash
GPT-4o-mini

Gemini 3.1 Flash Quirks & Gotchas

  • โ–ธMost cost-effective Google model โ€” ideal for high-volume pipelines
  • โ–ธContext caching available via Vertex AI for repeated document processing

GPT-4o-mini Quirks & Gotchas

  • โ–ธUltra-low latency โ€” best TTFT in the OpenAI lineup
  • โ–ธTool calling limited to single-step โ€” not suitable for complex agentic pipelines