Qwen2.5-VL 72B Instruct vs Qwen-VL OCR
Qwen-VL OCR comes out ahead, 36 to 30 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen2.5-VL 72B Instruct
30/100- ECI—
- Price$2.80 / $8.40
- Context131K
- Our pickAlibaba (Qwen)
Qwen-VL OCR
36/100- ECI—
- Price$0.72 / $0.72
- Context34K
Add a model
Make it a three-way comparison.
Qwen-VL OCR is our pick
Qwen-VL OCR is the better all-round choice, scoring 36/100 against Qwen2.5-VL 72B Instruct (30). It leads on price. Qwen2.5-VL 72B Instruct 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 priceQwen-VL OCRQwen-VL OCR $0.72 · Qwen2.5-VL 72B Instruct $4.20 per 1M tokens (3:1 blend)
- Longest contextQwen2.5-VL 72B InstructQwen2.5-VL 72B Instruct 131,072 · Qwen-VL OCR 34,096 tokens
- Widest inputsSame inputsQwen2.5-VL 72B Instruct: Text, Images · Qwen-VL OCR: Text, Images
- Self-hostingQwen2.5-VL 72B InstructPublishes downloadable weights
| Measure | Weight | Qwen2.5-VL 72B Instruct | Qwen-VL OCR |
|---|---|---|---|
| Price | 50% | 20 | 57 |
| Inputs & features | 30% | 50 | 25 |
| Context window | 20% | 24 | 1 |
| Overall | 100% | 30/100 | 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 | Qwen2.5-VL 72B InstructAlibaba (Qwen) | Qwen-VL OCRAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $2.80 | $0.72 (best) |
| Output | $8.40 | $0.72 (best) |
| Cached input | — | — |
| Blended (3:1) | $4.20 | $0.72 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Alibaba API |
| Limits | ||
| Context window | 131,072 tokens (best) | 34,096 tokens |
| Max output | 8,192 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | 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 | qwen2-5-vl-72b-instruct | qwen-vl-ocr |
| API providers | 1 | 1 |
| Released | Sep 2024 | Oct 28, 2024 |
| Knowledge cutoff | Apr 2024 | 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.
- Qwen2.5-VL 72B Instruct$44.80
- Qwen-VL OCR$8.64
Which should you choose?
Which is better: Qwen2.5-VL 72B Instruct or Qwen-VL OCR?
Qwen-VL OCR is the better all-round choice, scoring 36/100 against Qwen2.5-VL 72B Instruct (30). It leads on price. Qwen2.5-VL 72B Instruct 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, Qwen2.5-VL 72B Instruct or Qwen-VL OCR?
Qwen-VL OCR is cheaper at $0.72 input / $0.72 output per million tokens (official Alibaba API price). Qwen2.5-VL 72B Instruct costs $2.80 input / $8.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.72 per million tokens for Qwen-VL OCR versus $4.20 for Qwen2.5-VL 72B Instruct (5.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Qwen2.5-VL 72B Instruct 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 Qwen2.5-VL 72B Instruct 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?
Qwen2.5-VL 72B Instruct has the largest context window at 131,072 tokens, against 34,096 for Qwen-VL OCR. Maximum output per response: Qwen2.5-VL 72B Instruct up to 8,192, Qwen-VL OCR up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5-VL 72B Instruct accepts text and images; Qwen-VL OCR accepts text and images. They handle the same number of input types.
Are any of these open source?
Qwen2.5-VL 72B Instruct publishes its weights and can be self-hosted; Qwen-VL OCR is proprietary.
Which is newer?
Qwen-VL OCR is the newest, released Oct 28, 2024. Qwen2.5-VL 72B Instruct came out Sep 2024. Knowledge cutoff: Qwen2.5-VL 72B Instruct Apr 2024, 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.
Related comparisons
- Add Command R+Three-way comparison
- Qwen2.5-VL 72B Instruct vs Command R+Cohere
- Qwen2.5-VL 72B Instruct vs Palmyra X4Writer
- Qwen2.5-VL 72B Instruct vs Step 1 (32K)StepFun
- Qwen2.5-VL 72B Instruct vs Sonar Deep ResearchPerplexity
- Qwen-VL OCR vs Aya Expanse 32BCohere
- Qwen-VL OCR vs Llama 3.1 Nemotron 70B InstructNVIDIA
