o1-pro vs Phi-4-mini
Phi-4-mini comes out ahead, 58 to 27 on our weighted score, and it is the cheaper option too.
OpenAIo1-pro
27/100- ECI—
- Price$150.00 / $600.00
- Context200K
- Our pick
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
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Make it a three-way comparison.
Phi-4-mini is our pick
Phi-4-mini is the better all-round choice, scoring 58/100 against o1-pro (27). It leads on price. o1-pro wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest pricePhi-4-miniPhi-4-mini $0.131 · o1-pro $262.50 per 1M tokens (3:1 blend)
- Longest contexto1-proo1-pro 200,000 · Phi-4-mini 128,000 tokens
- Widest inputso1-proo1-pro: Text, Images · Phi-4-mini: Text
- Self-hostingPhi-4-miniPublishes downloadable weights
| Measure | Weight | o1-pro | Phi-4-mini |
|---|---|---|---|
| Price | 50% | 0 | 92 |
| Inputs & features | 30% | 70 | 25 |
| Context window | 20% | 32 | 24 |
| Overall | 100% | 27/100 | 58/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | o1-proOpenAI | Phi-4-miniMicrosoft |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $150.00 | $0.075 (best) |
| Output | $600.00 | $0.30 (best) |
| Cached input | — | — |
| Blended (3:1) | $262.50 | $0.131 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Azure API |
| Limits | ||
| Context window | 200,000 tokens (best) | 128,000 tokens |
| Max output | 100,000 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · medium · high | No |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | o1-pro | phi-4-mini |
| API providers | 5 (best) | 1 |
| Released | Mar 19, 2025 | Dec 11, 2024 |
| Knowledge cutoff | Sep 2023 | Oct 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o1-pro$2,700
- Phi-4-mini$1.35
Which should you choose?
Which is better: o1-pro or Phi-4-mini?
Phi-4-mini is the better all-round choice, scoring 58/100 against o1-pro (27). It leads on price. o1-pro wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, o1-pro or Phi-4-mini?
Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). o1-pro costs $150.00 input / $600.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.131 per million tokens for Phi-4-mini versus $262.50 for o1-pro (2001× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. o1-pro has not been scored yet and Phi-4-mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for o1-pro and Phi-4-mini yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
o1-pro has the largest context window at 200,000 tokens, against 128,000 for Phi-4-mini. Maximum output per response: o1-pro up to 100,000, Phi-4-mini up to 4,096 tokens.
Which can read images, PDFs, audio or video?
o1-pro accepts text and images; Phi-4-mini accepts text. o1-pro handles the widest range of inputs.
Are any of these open source?
Phi-4-mini publishes its weights and can be self-hosted; o1-pro is proprietary.
Which is newer?
o1-pro is the newest, released Mar 19, 2025. Phi-4-mini came out Dec 11, 2024. Knowledge cutoff: o1-pro Sep 2023, Phi-4-mini Oct 2023.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
