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Best vision model APIs for image understanding

Compare vision model APIs for screenshots, documents, product images, and support tickets, with price and capability labels.

Danh sach rut gon nay dung de lam gi?: Vision models

Vision APIs are useful for screenshots, receipts, product photos, and ticket attachments. What matters is whether the model accepts the image type you have, whether you need JSON out, and how wrong answers look on your own samples. Price second. The shortlist below is deliberately small — A/B a few vision-capable candidates instead of the whole catalog.

Co so nguon: NextModel capability mapping and OpenRouter input-modality metadata when available. · Cap nhat 2026-07-01

Fit score

Ung vien de xuat vision models

Bat dau voi danh sach rut gon, thu prompt thuc te va so sanh chi phi hang thang truoc khi routing production.

GoogleCatalogHealthytypical

‌Gemini 4 Argon via NextModel: 1M-token context; $2 / 1M tokens in / $10 / 1M tokens out per 1M tokens. Capabilities: streaming, tool, json.

$2 / 1M tokensInput$10 / 1M tokensOutput1MContext
Best forimage understanding, multimodal chat
StreamingTool callingJSON modeVisionLong context
Platform curatedCurated and maintained in the NextModel catalog
View details
AnthropicCatalogHealthyfast

Claude Haiku 5.5 via NextModel: 1M-token context; Starting at $0.1 / 1M tokens in / $0.5 / 1M tokens out per 1M tokens. Capabilities: streaming, tool, json.

Starting at $0.1 / 1M tokensInput$0.5 / 1M tokensOutput1MContext
Best forimage understanding, multimodal chat
StreamingTool callingJSON modeVisionLong context
Platform curatedCurated and maintained in the NextModel catalog
View details
DoubaoCatalog

Doubao Seedance 2.5 via NextModel: context unpublished; $0.225 / s in / — out per 1M tokens. Capabilities: streaming, vision.

$0.225 / sPer second—Context
Best forimage understanding, multimodal chat
StreamingVision
Platform curatedCurated and maintained in the NextModel catalog
View details
DreaminaCatalog

Dreamina-Seedance 2.0 Fast via NextModel: context unpublished; $0.122 / s in / — out per 1M tokens. Capabilities: streaming, vision.

$0.122 / sPer second—Context
Best forimage understanding, multimodal chat
StreamingVision
Platform curatedCurated and maintained in the NextModel catalog
View details

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So sanh danh sach rut gon theo gia, nha cung cap, context, kha nang va nguon.

Dung giao dien nay de thu hep shortlist production, xay dung chinh sach fallback hoac so sanh kinh te model.

ModelProviderInputOutputContextCapabilitiesBest forLatencyStatusSource
‌Gemini 4 Argongoogle/gemini-4-argonGoogle$2 / 1M tokens$10 / 1M tokens1M
StreamingTool callingJSON modeVision
image understanding, multimodal chat2974-10589msCatalogPlatform curated
Claude Haiku 5.5anthropic/claude-haiku-5.5AnthropicStarting at $0.1 / 1M tokens$0.5 / 1M tokens1M
StreamingTool callingJSON modeVision
image understanding, multimodal chat1321-2017msCatalogPlatform curated
Doubao Seedance 2.5doubao/doubao-seedance-2-5-260628Doubao$0.225 / s——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Dreamina-Seedance 2.0 Fastdreamina/dreamina-seedance-2-0-fast-260128Dreamina$0.122 / s——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Dreamina Seedance 2.5dreamina/dreamina-seedance-2-5-260628Dreamina$0.234 / s——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Gemini 3 Pro Image (Nano Banana Pro) gemini/gemini-3-pro-imageGemini$0.314 / image——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Gemini 3.1 Flash Image (Nano Banana 2)gemini/gemini-3.1-flash-imageGemini$0.151 / image——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Qwen-Image-2.0 CNqwen/qwen-image-2.0-cnQwen$0.0287 / image——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated

FAQ

Vision models FAQ

What should I compare before choosing a vision model API?

Image input support, JSON mode if you need it, latency, output cost, and quality on your real images. Synthetic benchmarks lie more often than people admit.

Can low-cost models handle vision tasks?

Sometimes, for light work. Dense documents and high-accuracy extraction usually need a stronger model and a real eval set.

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