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GPT-4o-mini vs o1

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 GPT-4o-mini and o1.

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...

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OpenAI

o1

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...

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Technical Specifications

SpecificationGPT-4o-minio1
ProviderOpenAIOpenAI
Context Window128,000 tokens200,000 tokens
Agent Suitability82/10088/100
Time to First Token (TTFT)150 ms2500 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-07-182024-12-17

API Pricing Comparison

Input Price per Million Tokens

GPT-4o-mini

$0.15

o1

$15.00

Output Price per Million Tokens

GPT-4o-mini

$0.60

o1

$60.00

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
8200.0%vs9180.0%
GPT-4o-mini
o1
HumanEvalPython coding & logic synthesis
8400.0%vs9450.0%
GPT-4o-mini
o1
MATHComplex mathematical problem solving
7020.0%vs9480.0%
GPT-4o-mini
o1
GPQAGraduate-level expert reasoning
4500.0%vs7830.0%
GPT-4o-mini
o1
HellaSwagCommonsense reasoning and inference
8470.0%vs9200.0%
GPT-4o-mini
o1
MT-BenchMulti-turn conversation flow quality
860.0%vs940.0%
GPT-4o-mini
o1

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

o1 Quirks & Gotchas

  • โ–ธReasoning model โ€” high latency by design, not for real-time use
  • โ–ธBest for complex math/code reasoning where accuracy > speed
  • โ–ธUse o3-mini when you need reasoning with lower latency