模型广场

Unifies generation and editing in one model; native 2K; professional typography and infographics.

上下文

待核

输入 / 1M tokens

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输出 / 1M tokens

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缓存读 / 1M

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缓存写 / 1M

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Fuses generation and editing; more professional text rendering and richer realistic textures and scenes.

上下文

待核

输入 / 1M tokens

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输出 / 1M tokens

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缓存读 / 1M

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缓存写 / 1M

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Stronger industrial design, geometric reasoning, and character consistency; text, object, and style edits.

上下文

待核

输入 / 1M tokens

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输出 / 1M tokens

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缓存读 / 1M

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缓存写 / 1M

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Multi-image input/output and custom resolution; multiple edited results per request.

上下文

待核

输入 / 1M tokens

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输出 / 1M tokens

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缓存读 / 1M

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缓存写 / 1M

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Diverse styles; multi-line layouts and paragraph-level text generation.

上下文

待核

输入 / 1M tokens

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输出 / 1M tokens

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缓存读 / 1M

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Instruction-tuned Qwen3 variant without thinking mode, strong on multilingual reasoning, math, code, and tool use for agent workflows.

上下文

262K

输入 / 1M tokens

$0.287

输出 / 1M tokens

$2.868

缓存读 / 1M

-

缓存写 / 1M

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Internal fine-tune of Qwen3-32B for text-only Chinese workloads, tuned to in-house instruction style for QA, summarization and rewriting.

上下文

131K

输入 / 1M tokens

$0.287

输出 / 1M tokens

$1.147

缓存读 / 1M

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缓存写 / 1M

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Qwen3-generation thinking-mode reasoning model with native tool use, tuned for math, coding, and multi-step agentic workflows.

上下文

262K

输入 / 1M tokens

$0.359

输出 / 1M tokens

$1.434

缓存读 / 1M

$0.072

缓存写 / 1M

$2.438

Deep-thinking preview that reasons step-by-step before answering, holding up on multi-step math, code, and Chinese-language tasks.

上下文

256K

输入 / 1M tokens

$0.861

输出 / 1M tokens

$3.441

缓存读 / 1M

$0.173

缓存写 / 1M

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Instruction-tuned non-thinking chat model that answers directly without exposing reasoning, suited to agent workflows needing deterministic output like coding assistance and tool calling.

上下文

262K

输入 / 1M tokens

$0.15

输出 / 1M tokens

$1.2

缓存读 / 1M

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缓存写 / 1M

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Lightweight multimodal model with balanced performance.

上下文

128K

输入 / 1M tokens

$0.25

输出 / 1M tokens

$0.75

缓存读 / 1M

$0.12

缓存写 / 1M

$0

Plus-tier vision-language model in the Qwen3-VL line, handling text, image and video inputs with strengths in document parsing, video understanding, spatial grounding and agent tool use.

上下文

262K

输入 / 1M tokens

$0.144

输出 / 1M tokens

$1.434

缓存读 / 1M

$0.029

缓存写 / 1M

$0.539

Open-weight mid-tier MoE text model with long chain-of-thought reasoning, strong on function-calling and multi-step planning benchmarks for self-hosted agentic workflows.

上下文

262K

输入 / 1M tokens

$0.115

输出 / 1M tokens

$0.917

缓存读 / 1M

$0

缓存写 / 1M

$0

Mid-tier Qwen model tuned for multi-step reasoning and agent workflows, compact enough for private and on-prem deployment.

上下文

262K

输入 / 1M tokens

$0.086

输出 / 1M tokens

$0.688

缓存读 / 1M

$0

缓存写 / 1M

$0

Lightweight mid-tier variant tuned for low-latency agent workflows with coding and tool-calling support.

上下文

1M

输入 / 1M tokens

$0.029

输出 / 1M tokens

$0.287

缓存读 / 1M

$0.003

缓存写 / 1M

$0.036

Multimodal model from the Qwen3.5 line with toggleable thinking mode, tuned for image and video understanding, document parsing, and multimodal agents.

上下文

1M

输入 / 1M tokens

$0.115

输出 / 1M tokens

$0.688

缓存读 / 1M

$0.057

缓存写 / 1M

$0.717

Thinking-mode variant of the dense open-weight model that outputs step-by-step reasoning; at 27B it surpasses the prior open-weight 397B-A17B flagship across coding, math and multi-step reasoning benchmarks.

上下文

262K

输入 / 1M tokens

$0.412564

输出 / 1M tokens

$2.475384

缓存读 / 1M

$0

缓存写 / 1M

$0

Open-weight coding model tuned for agentic terminal tasks and repo-scale reasoning with low inference cost.

上下文

262K

输入 / 1M tokens

$0.248

输出 / 1M tokens

$1.485

缓存读 / 1M

-

缓存写 / 1M

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Qwen 3.6 lightweight tier with text, image, and video input. Low latency and low cost, well-suited for high-volume classification, extraction, summarization, and simple agent workflows.

上下文

1M

输入 / 1M tokens

$0.165

输出 / 1M tokens

$0.99

缓存读 / 1M

$0

缓存写 / 1M

$0

Enhanced Qwen model with strong bilingual (Chinese/English) comprehension, excelling at long-document analysis and structured output.

上下文

1M

输入 / 1M tokens

$0.276

输出 / 1M tokens

$1.651

缓存读 / 1M

$0

缓存写 / 1M

$0

Qwen3.7 Flash is the lightweight tier in the series, a vision-language reasoning model with strengths in object recognition, spatial understanding, and real-world visual perception. Suited for multimodal agents, visual coding, search, and computer interaction.

上下文

1M

输入 / 1M tokens

$0.03

输出 / 1M tokens

$0.13

缓存读 / 1M

$0.006

缓存写 / 1M

$0.038

Flagship agent-centric reasoning model with a 1M context window, excelling at coding, productivity, and long-horizon autonomous tasks.

上下文

1M

输入 / 1M tokens

$1.65

输出 / 1M tokens

$4.951

缓存读 / 1M

$0.33

缓存写 / 1M

$2.063

Qwen 3.7 Plus is a mid-tier multimodal model that reads screens, operates GUIs, and navigates mobile apps end-to-end. Suited for agent workflows and tool calling.

上下文

1M

输入 / 1M tokens

$0.276

输出 / 1M tokens

$1.101

缓存读 / 1M

$0.056

缓存写 / 1M

$0

Flash tier in Qwen3.8: multimodal reasoning for coding and agent workflows, with visual understanding across documents, codebases, and long video.

上下文

1M

输入 / 1M tokens

$0.113

输出 / 1M tokens

$0.382

缓存读 / 1M

$0.014

缓存写 / 1M

$0.177

Qwen3.8 series flagship, the general-availability successor to Max Preview. A multimodal reasoning model built for complex reasoning, visual understanding, coding, and agentic workflows.

上下文

1M

输入 / 1M tokens

$2

输出 / 1M tokens

$6

缓存读 / 1M

$0.25

缓存写 / 1M

$2.5