Phi-4-mini vs Qwen-VL OCR
Phi-4-mini comes out ahead, 58 to 36 on our weighted score, and it is the cheaper option too.
- Our pick
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
Alibaba (Qwen)Qwen-VL OCR
36/100- ECI—
- Price$0.72 / $0.72
- Context34K
Add a model
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 Qwen-VL OCR (36). It leads on price 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 · Qwen-VL OCR $0.72 per 1M tokens (3:1 blend)
- Longest contextPhi-4-miniPhi-4-mini 128,000 · Qwen-VL OCR 34,096 tokens
- Widest inputsQwen-VL OCRPhi-4-mini: Text · Qwen-VL OCR: Text, Images
- Self-hostingPhi-4-miniPublishes downloadable weights
| Measure | Weight | Phi-4-mini | Qwen-VL OCR |
|---|---|---|---|
| Price | 50% | 92 | 57 |
| Inputs & features | 30% | 25 | 25 |
| Context window | 20% | 24 | 1 |
| Overall | 100% | 58/100 | 36/100 |
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 | Phi-4-miniMicrosoft | Qwen-VL OCRAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.075 (best) | $0.72 |
| Output | $0.30 (best) | $0.72 |
| Cached input | — | — |
| Blended (3:1) | $0.131 (best) | $0.72 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Azure API | Official Alibaba API |
| Limits | ||
| Context window | 128,000 tokens (best) | 34,096 tokens |
| Max output | 4,096 tokens | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | No |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | phi-4-mini | qwen-vl-ocr |
| API providers | 1 | 1 |
| Released | Dec 11, 2024 | Oct 28, 2024 |
| Knowledge cutoff | Oct 2023 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Phi-4-mini$1.35
- Qwen-VL OCR$8.64
Which should you choose?
Which is better: Phi-4-mini or Qwen-VL OCR?
Phi-4-mini is the better all-round choice, scoring 58/100 against Qwen-VL OCR (36). It leads on price 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, Phi-4-mini or Qwen-VL OCR?
Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). Qwen-VL OCR costs $0.72 input / $0.72 output per million tokens (official Alibaba 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 $0.72 for Qwen-VL OCR (5.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Phi-4-mini has not been scored yet and Qwen-VL OCR has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Phi-4-mini and Qwen-VL OCR yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-VL OCR does not support tool calling, which most coding agents need.
Which has the bigger context window?
Phi-4-mini has the largest context window at 128,000 tokens, against 34,096 for Qwen-VL OCR. Maximum output per response: Phi-4-mini up to 4,096, Qwen-VL OCR up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Phi-4-mini accepts text; Qwen-VL OCR accepts text and images. Qwen-VL OCR handles the widest range of inputs.
Are any of these open source?
Phi-4-mini publishes its weights and can be self-hosted; Qwen-VL OCR is proprietary.
Which is newer?
Phi-4-mini is the newest, released Dec 11, 2024. Qwen-VL OCR came out Oct 28, 2024. Knowledge cutoff: Phi-4-mini Oct 2023, Qwen-VL OCR Apr 2024.
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.
