Most people are still using text-only AI models. But the multimodal models available in 2026 are genuinely good — and surprisingly affordable. I tested six vision-capable models across image description, OCR extraction, visual question answering, and document understanding.
The Contenders
| Model | Input $/M | Image Desc | OCR | VQA | Docs |
|---|---|---|---|---|---|
| Qwen-VL-Max | $2.80 | ★★★★★ | ★★★★★ | ★★★★★ | ★★★★★ |
| Qwen-VL-Plus | $0.80 | ★★★★ | ★★★★ | ★★★★ | ★★★★ |
| GLM-4V | $1.50 | ★★★★ | ★★★★★ | ★★★★ | ★★★★ |
| Hunyuan-Vision | $0.55 | ★★★ | ★★★ | ★★★ | ★★★ |
| MiniMax-VL-01 | $1.21 | ★★★★ | ★★★ | ★★★★ | ★★★ |
My Recommendation
For most developers, Qwen-VL-Plus is the sweet spot. At $0.80/M input, it handles image description extremely well, OCR is nearly flawless, and document understanding is very good. The Max version is better but 3.5x more expensive — only worth it if you're processing medical images or highly technical diagrams.
For budget-conscious projects, Hunyuan-Vision at $0.55/M is surprisingly capable. It's not the best at anything, but it's good enough for simple use cases like product image classification.
# Vision API via Global API
client = OpenAI(api_key="ga_...", base_url="https://global-apis.com/v1")
response = client.chat.completions.create(
model="Qwen/Qwen-VL-Plus",
messages=[{"role":"user","content":[
{"type":"text","text":"Describe this image"},
{"type":"image_url","image_url":{"url":"https://..."}}
]}]
)All multimodal models accessed through Global API. Same OpenAI-compatible endpoint, just change the model name.