Qwen-VL OCR vs Phi-4-mini vs Aya Expanse 32B
Phi-4-mini comes out ahead, 58 to 36 and 33 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen-VL OCR
36/100- ECI—
- Price$0.72 / $0.72
- Context34K
- Our pick
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
CohereAya Expanse 32B
33/100- ECI—
- Price$0.50 / $1.50
- Context128K
Phi-4-mini is our pick
Phi-4-mini is the better all-round choice, scoring 58/100 against Qwen-VL OCR (36) and Aya Expanse 32B (33). It leads on price. 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 · Aya Expanse 32B $0.75 per 1M tokens (3:1 blend)
- Longest contextPhi-4-mini and Aya Expanse 32BPhi-4-mini 128,000 · Aya Expanse 32B 128,000 · Qwen-VL OCR 34,096 tokens
- Widest inputsQwen-VL OCRQwen-VL OCR: Text, Images · Phi-4-mini: Text · Aya Expanse 32B: Text
- Self-hostingPhi-4-mini and Aya Expanse 32BPublishes downloadable weights (CC-BY-NC-4.0)
| Measure | Weight | Qwen-VL OCR | Phi-4-mini | Aya Expanse 32B |
|---|---|---|---|---|
| Price | 50% | 57 | 92 | 56 |
| Inputs & features | 30% | 25 | 25 | 0 |
| Context window | 20% | 1 | 24 | 24 |
| Overall | 100% | 36/100 | 58/100 | 33/100 |
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 | Qwen-VL OCRAlibaba (Qwen) | Phi-4-miniMicrosoft | Aya Expanse 32BCohere |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.72 | $0.075 (best) | $0.50 |
| Output | $0.72 | $0.30 (best) | $1.50 |
| Cached input | — | — | — |
| Blended (3:1) | $0.72 | $0.131 (best) | $0.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Azure API | Median of 1 providers |
| Limits | |||
| Context window | 34,096 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Max output | 4,096 tokens (best) | 4,096 tokens (best) | 4,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | OpenCC-BY-NC-4.0 |
| API model ID | qwen-vl-ocr | phi-4-mini | c4ai-aya-expanse-32b |
| API providers | 1 | 1 | 2 (best) |
| Released | Oct 28, 2024 | Dec 11, 2024 | Oct 24, 2024 |
| Knowledge cutoff | Apr 2024 | 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.
- Qwen-VL OCR$8.64
- Phi-4-mini$1.35
- Aya Expanse 32B$8.00
Which should you choose?
Which is better: Qwen-VL OCR, Phi-4-mini or Aya Expanse 32B?
Phi-4-mini is the better all-round choice, scoring 58/100 against Qwen-VL OCR (36) and Aya Expanse 32B (33). It leads on price. 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, Qwen-VL OCR, Phi-4-mini or Aya Expanse 32B?
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); Aya Expanse 32B costs $0.50 input / $1.50 output per million tokens (median across 1 API provider). 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) and $0.75 for Aya Expanse 32B (5.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen-VL OCR has not been scored yet, Phi-4-mini has not been scored yet and Aya Expanse 32B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen-VL OCR, Phi-4-mini and Aya Expanse 32B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-VL OCR and Aya Expanse 32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Phi-4-mini and Aya Expanse 32B have the largest context windows (128,000 and 128,000 tokens), against 34,096 for Qwen-VL OCR. Maximum output per response: Qwen-VL OCR up to 4,096, Phi-4-mini up to 4,096, Aya Expanse 32B up to 4,000 tokens.
Which can read images, PDFs, audio or video?
Qwen-VL OCR accepts text and images; Phi-4-mini accepts text; Aya Expanse 32B accepts text. Qwen-VL OCR handles the widest range of inputs.
Are any of these open source?
Phi-4-mini and Aya Expanse 32B publishes its weights (CC-BY-NC-4.0) 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; Aya Expanse 32B came out Oct 24, 2024. Knowledge cutoff: Qwen-VL OCR Apr 2024, 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.
