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seed-character

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bytedance

Character roleplay model for virtual companion scenarios, with stable persona adherence and plot progression in multi-turn dialogue, supporting multimodal inputs.

上下文
128K
输入 / 1M tokens
$0.12
输出 / 1M tokens
$0.29
缓存读 / 1M
$0.02
缓存写 / 1M
$0
ChatVisionChineseCreative Generation

doubao-seed-2.0-mini-260428

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bytedance

Lightweight tier in the Seed 2.0 family, tuned for high-throughput, low-latency tasks with adjustable reasoning levels. Fits batch processing, moderation, and classification.

上下文
256K
输入 / 1M tokens
$0.1
输出 / 1M tokens
$0.4
缓存读 / 1M
$0.02
缓存写 / 1M
$0.008333
Real-time ResponseLightweightClassificationBatch Generation

deepseek-v3.2

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DeepSeek

Best value for code and math. Fraction of flagship cost.

上下文
164K
输入 / 1M tokens
$0.287
输出 / 1M tokens
$0.431
缓存读 / 1M
$0.058
缓存写 / 1M
$0.359
CodingMathCost Effective

deepseek-v3.2-exp

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DeepSeek

Experimental interim release focused on long-context efficiency, with optional reasoning mode and V3.1-level performance overall.

上下文
164K
输入 / 1M tokens
$0.287
输出 / 1M tokens
$0.43
缓存读 / 1M
$0
缓存写 / 1M
$0
ReasoningLong Text ProcessingChain of ThoughtDeep Analysis

gemini-2.5-flash-lite

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Google

A lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency, with faster token generation and higher throughput. Thinking is disabled by default but can be enabled via API.

上下文
1.1M
输入 / 1M tokens
$0.1
输出 / 1M tokens
$0.4
缓存读 / 1M
$0.01
缓存写 / 1M
$0.08333
FinanceCodingTranslation

gemma-4-31b

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Google

Open-weights dense model with stronger math and coding, plus native function calling for self-hosted agent workflows.

上下文
262K
输入 / 1M tokens
$0.14
输出 / 1M tokens
$0.4
缓存读 / 1M
$0
缓存写 / 1M
$0
CodingMathLocal DeploymentAgent

gpt-4.1-nano

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OpenAI

Fastest GPT. Sub-second responses.

上下文
1M
输入 / 1M tokens
$0.1
输出 / 1M tokens
$0.4
缓存读 / 1M
$0.025
缓存写 / 1M
-
Cost Effective

gpt-5-nano

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OpenAI

Cheapest GPT. Built for high-volume simple jobs.

上下文
400K
输入 / 1M tokens
$0.05
输出 / 1M tokens
$0.4
缓存读 / 1M
$0.01
缓存写 / 1M
$0
Cost Effective

qwen3.5-flash

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qwen

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
CodingLong Text ProcessingReal-time ResponseLightweight

qwen3.8-flash

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qwen

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
ReasoningVisionCodingMultimodal Understanding

step-3.5-flash

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stepfun

StepFun’s most capable open-source foundation model, built on a sparse MoE architecture that activates only 11B of its 196B parameters per token. It delivers efficient reasoning and fast performance, even with long contexts.

上下文
256K
输入 / 1M tokens
$0.1
输出 / 1M tokens
$0.3
缓存读 / 1M
$0
缓存写 / 1M
$0
CodingTranslationFinance

mimo-v2.5

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xiaomi

Mid-tier V2.5 model with native image, audio, and video understanding, built for agent workflows and coding at lower cost than Pro.

上下文
1M
输入 / 1M tokens
$0.14
输出 / 1M tokens
$0.28
缓存读 / 1M
$0.0428
缓存写 / 1M
$0
CodingMultimodal UnderstandingAgent CodingAgent

glm-4.7-flash

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Z.ai

Ultra-fast for Chinese. Very cheap.

上下文
203K
输入 / 1M tokens
$0.1
输出 / 1M tokens
$0.43
缓存读 / 1M
$0.01
缓存写 / 1M
$0
ChineseCost Effective
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