Σύντομη λίστα μοντέλων

Best vision model APIs for image understanding

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

Σε τι χρησιμεύει αυτή η σύντομη λίστα;: 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.

Βάση πηγής: NextModel capability mapping and OpenRouter input-modality metadata when available. · Ενημερώθηκε 2026-07-01

Fit score

Προτεινόμενοι υποψήφιοι vision models

Ξεκινήστε από τη σύντομη λίστα, δοκιμάστε πραγματικά prompt και συγκρίνετε το μηνιαίο κόστος πριν από τη δρομολόγηση στην παραγωγή.

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Doubao Seedance 2.5 via NextModel: context unpublished; $0.225 / s in / — out per 1M tokens.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Dreamina-Seedance 2.0 Fast via NextModel: context unpublished; $0.122 / s in / — out per 1M tokens.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

Πίνακας σύγκρισης

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Χρησιμοποιήστε αυτή την προβολή όταν περιορίζετε τη λίστα για παραγωγή, χτίζετε εφεδρική πολιτική ή συγκρίνετε την οικονομία των μοντέλων.

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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