o1-preview vs Phi 4
o1-preview leads the LLM Stats Score 16.7 to 5.5. Phi 4 is 300.0x cheaper per token.
OpenAI · Microsoft · Updated for 2026
Which is better?
o1-preview leads the overall LLM Stats Score 16.7 to 5.5, ranking #218 overall.
In the 6 individual benchmarks reported for both models, o1-preview wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, Phi 4 is roughly 300.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o1-preview also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose o1-preview
- overall performance matters — it scores 16.7 and ranks #218 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 6 exact shared results
- you process long inputs — it offers a 128,000 token context window
Choose Phi 4
- cost matters — it's about 300.0x cheaper per token
- you want the most recent training data — it shipped Dec 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for o1-preview · 13 for Phi 4
o1-preview outperforms in 6 benchmarks (GPQA, LiveBench, MATH, MGSM, MMLU, SimpleQA), while Phi 4 is better at 0 benchmarks.
o1-preview significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, o1-preview ($15.00/1M tokens) is 214.3x more expensive than Phi 4 ($0.07/1M tokens).
For output processing, o1-preview ($60.00/1M tokens) is 428.6x more expensive than Phi 4 ($0.14/1M tokens).
In conclusion, o1-preview is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o1-preview accepts 128,000 input tokens compared to Phi 4's 16,000 tokens. o1-preview can generate longer responses up to 32,768 tokens, while Phi 4 is limited to 16,000 tokens.
License
Usage and distribution terms
o1-preview is licensed under a proprietary license, while Phi 4 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
o1-preview was released on 2024-09-12, while Phi 4 was released on 2024-12-12.
Phi 4 is 3 months newer than o1-preview.
Sep 12, 2024
2.0 years ago
Dec 12, 2024
1.7 years ago
3mo newerKnowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while o1-preview's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without o1-preview's cutoff date.
—
Jun 2024
Provider Availability
o1-preview is available from OpenAI, Azure. Phi 4 is available from DeepInfra.
o1-preview
Phi 4
Outputs Comparison
Judge for yourself.
Run your own prompts against o1-preview and Phi 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about o1-preview vs Phi 4.