รายชื่อโมเดลตัวเลือก

Best vision model APIs for image understanding

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

รายชื่อนี้เหมาะกับการใช้งานแบบไหน?: 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.

พื้นฐานของแหล่งข้อมูล: NextModel capability mapping and OpenRouter input-modality metadata when available. · อัปเดตล่าสุด 2026-07-01

Fit score

ตัวเลือกที่แนะนำ vision models

เริ่มจากรายชื่อโมเดลตัวเลือก จากนั้นทดสอบด้วย prompt จริง และเปรียบเทียบค่าใช้จ่ายรายเดือนก่อนนำไปใช้กับ production routing

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Doubao Seedance 2.5 via NextModel: context unpublished; $0.225 / s in / — out per 1M tokens.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Dreamina-Seedance 2.0 Fast via NextModel: context unpublished; $0.122 / s in / — out per 1M tokens.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

ตารางเปรียบเทียบ

เปรียบเทียบรายชื่อโมเดลตามราคา ผู้ให้บริการ context ความสามารถ และแหล่งข้อมูล

ใช้มุมมองนี้เมื่อคุณกำลังคัด shortlist สำหรับ production สร้างนโยบาย fallback หรือเปรียบเทียบความคุ้มค่าของโมเดล

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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