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o1-mini vs Phi-4: Benchmarks, Pricing, and Context Window Comparison

o1-mini vs Phi-4 compares provider, context window, token pricing, benchmark performance, and release timeline in one side-by-side view. Use this page to quickly identify which model is a better fit for your production constraints, quality targets, and estimated cost per request.

Verdict

Phi-4 has lower listed token pricing, while o1-mini can still be preferable if benchmark results better match your workload.

Author: Mirai Minds Research Team

Last updated:

Sources

Compare
o1-mini
to
Phi-4
Overview
o1-mini was released 3 months before Phi-4.
o1-mini
Phi-4
Provider
The entity that provides this model.
OpenAI
Microsoft
Input Context Window
The number of tokens supported by the input context window.
128000
tokens
4,000
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
65536
tokens
4,000
tokens
Release Date
When the model was first released.
2024-09-12
2024-12-12
Leaderboard
o1-mini
Phi-4
Rank
5
Unknown
Arena Elo
1307
Not specified.
95% CI
+3/-4
Not specified.
Votes
35691
Not specified.
License
Proprietary
Microsoft Research License Agreement
Knowledge Cutoff
4/2023
Unknown
Pricing
o1-mini
Phi-4
Input
Cost of input data provided to the model.
$1.10
per million tokens
$0.125
per million tokens
Output
Cost of output tokens generated by the model.
$4.40
per million tokens
$0.5
per million tokens
Benchmarks
Compare relevant benchmarks between o1-mini and Phi-4 Instruct.
o1-mini
Phi-4
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
85.2
(5-shot)
Source
Benchmark not available.
MMMU
A wide ranging multi-discipline and multimodal benchmark.
Benchmark not available.
Benchmark not available.
HellaSwag
A challenging sentence completion benchmark.
Benchmark not available.
Benchmark not available.

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sneh[at]miraiminds.co

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