Is GPT-4o mini cheaper than o1-mini?

On input tokens, GPT-4o mini is cheaper ($0.15 vs $3.00 per million). On output tokens, GPT-4o mini is cheaper. Total cost on a typical workload depends on your input:output ratio.

Which has the larger context window, GPT-4o mini or o1-mini?

o1-mini has a 128,000-token context window. GPT-4o mini fits 128,000 tokens.

How do I switch from GPT-4o mini to o1-mini?

Update the model id in your API call: replace "gpt-4o-mini" with "o1-mini". Then verify cost impact on a sample of your real prompts using a token counter.

GPT-4o mini vs o1-mini

Side-by-side comparison of GPT-4o mini (OpenAI) and o1-mini (OpenAI). Exact API pricing per million tokens, context windows, output speed, and total cost on real-world prompts.

Specifications

Spec	GPT-4o mini	o1-mini
Provider	OpenAI	OpenAI
Model id	gpt-4o-mini	o1-mini
Input price (per 1M tokens)	$0.15	$3.00
Output price (per 1M tokens)	$0.60	$12.00
Context window	128,000	128,000
Output speed (tokens/sec)	~130	~65
Tokenizer encoding	o200k_base	o200k_base

Cost on real prompts

Total cost = (input tokens × input price) + (output tokens × output price). Numbers below use the exact pricing tables published by each provider.

Scenario	Input	Output	GPT-4o mini	o1-mini	Cheaper
Short question + answer	50	150	$0.000097	$0.001950	GPT-4o mini
Code review on one file	500	1,500	$0.000975	$0.019500	GPT-4o mini
Long document summary	5,000	500	$0.001050	$0.021000	GPT-4o mini
Heavy reasoning task	2,000	8,000	$0.005100	$0.102000	GPT-4o mini
Full codebase analysis	50,000	10,000	$0.013500	$0.270000	GPT-4o mini

Want the exact cost for your prompt instead of these examples? Open the cost calculator pre-loaded with both models →

When to pick which

Heuristics derived from the spec table above. Always validate on your own prompts before committing — these are starting points, not verdicts.

Pick GPT-4o mini for

•output-heavy workloads (long-form generation, code, summaries) — gpt-4o-mini is meaningfully cheaper per output token
•input-heavy workloads (long context, RAG, document QA) — gpt-4o-mini is cheaper per input token
•latency-sensitive UX (chat, autocompletion) — gpt-4o-mini streams faster (~130 vs ~65 tok/s)

Pick o1-mini for

•complex multi-step reasoning — o1-mini uses chain-of-thought internally

Switching between them

For most use cases, switching providers means updating the model id and the request shape if the providers differ. Within the same provider, it's usually a single-line change.

From GPT-4o mini to o1-mini

# Before
model = "gpt-4o-mini"

# After
model = "o1-mini"

If the providers differ (OpenAI vs OpenAI), you'll also need to swap the SDK / endpoint URL. Cross-provider migrations usually take 30 minutes to a few hours depending on how many features (streaming, function calling, tool use) you depend on.

Calculate cost on your own prompt

The examples above use generic input/output ratios. For an exact comparison, paste your real prompt into the calculator — it counts tokens with the right tokenizer for each model and shows side-by-side cost.

Open the calculator with both models →