即將推出
先參考上方的單次執行預估,再查看完整的 CometAPI 與官方價格比較。
探索 Qwen-Image-3.0 的競爭性定價,專為滿足各種預算和使用需求而設計。我們靈活的方案確保您只需為實際使用量付費,讓您能夠隨著需求增長輕鬆擴展。了解 Qwen-Image-3.0 如何在保持成本可控的同時提升您的專案效果。
| Comet Price (USD / M Tokens) | Official Price (USD / M Tokens) | Discount |
|---|---|---|
輸入:$60/M 輸出:$60/M | 輸入:$75/M 輸出:$75/M | -20% |
複製可用的端點與程式碼範例,需要完整參數時再開啟完整 API 參考文件。
存取完整的範例程式碼和 API 資源,以簡化您的 Qwen-Image-3.0 整合流程。我們詳盡的文件提供逐步指引,協助您在專案中充分發揮 Qwen-Image-3.0 的潛力。
#!/usr/bin/env bash
set -euo pipefail
: "${COMETAPI_KEY:?Set COMETAPI_KEY before running this example}"
: "${QWEN_IMAGE_INPUT_URL:?Set QWEN_IMAGE_INPUT_URL before running this example}"
generation_payload=$(jq -nc \
--arg model "qwen-image-3.0" \
'{
model: $model,
input: {
messages: [{
role: "user",
content: [{
text: "Create a cinematic watercolor of a moonlit harbor with glowing paper lanterns."
}]
}]
},
parameters: {
negative_prompt: "blurry, low quality",
prompt_extend: true,
watermark: false,
size: "1328*1328"
}
}')
echo "Generation response:"
curl --fail-with-body --silent --show-error --request POST \
https://api.cometapi.com/v1/images/generations \
--header "Authorization: Bearer ${COMETAPI_KEY}" \
--header "Content-Type: application/json" \
--data "${generation_payload}"
echo
edit_payload=$(jq -nc \
--arg model "qwen-image-3.0" \
--arg image "${QWEN_IMAGE_INPUT_URL}" \
'{
model: $model,
input: {
messages: [{
role: "user",
content: [
{image: $image},
{text: "Turn the scene into a moonlit watercolor while preserving the main composition."}
]
}]
},
parameters: {
n: 1,
negative_prompt: "blurry, low quality",
prompt_extend: true,
watermark: false
}
}')
echo "Edit response:"
curl --fail-with-body --silent --show-error --request POST \
https://api.cometapi.com/v1/images/edits \
--header "Authorization: Bearer ${COMETAPI_KEY}" \
--header "Content-Type: application/json" \
--data "${edit_payload}"
echo在選擇架構或評估正式環境負載前,先掌握模型的關鍵資訊。
將 Qwen-Image-3.0 用於符合其 image 能力的正式工作流程,並在長期整合前比較其他選項。
產品視覺與行銷素材創作
概念圖與快速視覺探索
圖像編輯、變化與素材產製
比較 CometAPI 提供的其他模型,在品質、延遲、功能與價格間取得平衡。
OpenAI 最強大的圖像生成模型,具備跨多語言近乎完美的文字渲染、最高可達 4K 解析度,以及由推理驅動的 Thinking Mode。專為對準確性、速度與符合品牌調性的視覺輸出有嚴格要求的生產級工作流程而打造。
Gemini 3.1 Flash Lite Image model 是圖像生成系列中的效率專家,專為超低延遲與具成本效益的圖像生成與修改而設計。
Core Capabilities Overview: Resolution: Up to 4K (4096×4096), on par with Pro. Reference Image Consistency: Up to 14 reference images (10 objects + 4 characters), maintaining style/character consistency. Extreme Aspect Ratios: New 1:4, 4:1, 1:8, 8:1 ratios added, suitable for long images, posters, and banners. Text Rendering: Advanced text generation, suitable for infographics and marketing poster layouts. Search Enhancement: Integrated Google Search + Image Search. Grounding: Built-in thinking process; complex prompts are reasoned before generation.
FLUX.2 [max] is a top-tier visual-intelligence model from Black Forest Labs (BFL) designed for production workflows: marketing, product photography, e-commerce, creative pipelines, and any application that requires consistent character/product identity, accurate text rendering, and photoreal detail at multi-megapixel resolutions. The architecture is engineered for strong prompt-following, multi-reference fusion (up to ten input images), and grounded generation (ability to incorporate up-to-date web context when producing images).
FLUX.2 [max] is the flagship, highest-quality variant of the FLUX.2 family from Black Forest Labs (BFL). It is positioned as a professional-grade text→image generation and image-editing model that focuses on maximal fidelity, prompt adherence, and editing consistency across characters, objects, lighting and color. BFL and partner registries describe FLUX.2 [max] as the top-tier FLUX.2 variant with features for multi-reference editing, grounded generation.
FLUX 2 DEV is the development-friendly version optimized for research, experimentation, and non-commercial applications. It provides developers with powerful image generation capabilities while maintaining a balance between quality and computational efficiency. Perfect for prototyping, academic research, and personal creative projects.
在正式上線前,查看即時心跳資料、端點可用性與實測回應時間。