o3-mini vs Phi-4
A complete head-to-head: pricing, context window, benchmarks, modality coverage, and openness, with a programmatic verdict synthesized from the underlying data.
Updated
o3-mini specs · Phi-4 specs- Priceo3-mini
o3-mini publishes pricing ($4.40 / 1M output tokens) while Phi-4 does not.
- Context windowo3-mini
o3-mini accepts 200K tokens vs 16K, 12.5× the room for long documents and codebases.
- BenchmarksTie
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores.
- ModalitiesTie
Both handle text.
- OpennessPhi-4
Phi-4 ships open weights (MIT); o3-mini is API-only.
On balance o3-mini edges ahead, winning 2 of 5 categories against Phi-4's 1. o3-mini publishes pricing ($4.40 / 1M output tokens) while Phi-4 does not. o3-mini accepts 200K tokens vs 16K, 12.5× the room for long documents and codebases.
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores. Both target the same set of modalities (text), so the deciding factors are price, context, and raw quality. Phi-4 ships open weights (MIT); o3-mini is API-only.
o3-mini is the newer of the two, released 2 months after Phi-4, which usually means a more recent knowledge cutoff and updated safety post-training. o3-mini is usually picked for reasoning and math workloads, while Phi-4 sees more deployments in on device and edge deployment. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.
Side-by-side specs
| Spec | o3-mini | Phi-4 |
|---|---|---|
| Provider | OpenAI | Microsoft |
| Released | Jan 2025 | Dec 2024 |
| Modalities | text | text |
| Context window | 200K tokens | 16K tokens |
| Max output | , | , |
| Input · 1M | $1.10 / 1M tokens | Pricing not published |
| Output · 1M | $4.40 / 1M tokens | Pricing not published |
| Knowledge cutoff | 2023-10 | , |
| Open weights | No | Yes (MIT) |
| API available | Yes | Yes |
Pricing at scale
What you'd actually pay at typical workloads. Numbers come from each model's published per-million-token rates.
- Light usage, 100k in / 50k out per day$9.90 vs ,
- Heavy usage, 1M in / 500k out per day$99.00 vs ,
- RAG workload, 5M in / 200k out per day$191 vs ,
Light usage, 100k in / 50k out per day: pricing not directly comparable (one or both models are missing public per-token rates). Heavy usage, 1M in / 500k out per day: pricing not directly comparable (one or both models are missing public per-token rates). RAG workload, 5M in / 200k out per day: pricing not directly comparable (one or both models are missing public per-token rates).
Estimated spend for the listed models at your usage. Numbers are derived from each model's published per-million-token rates.
- o3-mini$0.330
- Phi-4Pricing unavailable
Benchmarks compared
Only sourced numbers. Where a benchmark is missing for one model we show the available value rather than fabricating the other.
- MMLU,84.8
- HumanEval,82.6
- GPQA79.7
o3-mini fits when…
- Reasoning at mid-tier cost
- Fast for a thinking model
- Long-context tasks, handles 200K tokens vs 16K for Phi-4.
Phi-4 fits when…
- Exceptional quality at 14B parameters
- MIT license, clean commercial use
- Strong on math
- Self-hosting and on-prem requirements, open weights (MIT).
Consider GPT-5.5
OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.
Frequently asked
Is o3-mini or Phi-4 cheaper?
Per-token pricing isn't published for at least one of these models, check each model's spec page for current rates.Which has the larger context window?
o3-mini accepts 200K tokens vs 16K for Phi-4.Is o3-mini or Phi-4 better for coding?
Both o3-mini and Phi-4 are competitive on coding benchmarks. See each model's individual spec page for HumanEval and SWE-bench scores where published. For an opinionated pick, consult our Best LLM for Coding ranking.Are either of these models open source?
Phi-4 ships open weights (MIT). o3-mini is API-only.When were o3-mini and Phi-4 released?
o3-mini was released by OpenAI on 2025-01-31. Phi-4 was released by Microsoft on 2024-12-12.
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