AI 模型情报

DeepSeek Reasoner

deepseek/reasoner

出品方: DeepSeek · 系列: deepseek-thinking · 发布 2025-01-20 · 知识截止: 2024-07

$0.140
输入 / 1M token
$0.280
输出 / 1M token
1M
上下文长度
384K
最大输出

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

能力清单

工具调用推理? 结构化输出附件开放权重温度可调
支持模态: 输入 text · 输出 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding74
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)20/20
  • Provider availability4/10
Agents69
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability4/10
JSON / structured output49
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume19/20
Cost efficiency77
  • Headline price (log-scaled)72/95
  • Has prompt-cache pricing5/5
Long context90
  • Context window (100K → 2M)80/90
  • Has published price for full window10/10
Production-readiness76
  • Number of independent providers20/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers6/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$0.84
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$1.68
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$0.42
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$1.40
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$1.85
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定价详情

推荐定价来自 deepseek · deepseek-reasoner

$0.140
输入
$0.280
输出
$0.028
缓存读

在 4 家渠道可用

服务商服务商模型 ID输入 / 1M输出 / 1M上下文发布日期
DeepSeek
deepseek
deepseek-reasoner$0.140$0.2801M2025-12-01
302.AI
302ai
deepseek-reasoner$0.290$0.430128K2025-01-20
NanoGPT
nano-gpt
deepseek-reasoner$0.400$1.7064K2025-01-20
Helicone
helicone
deepseek-reasoner$0.560$1.68128K2025-01-20

各渠道数据存在不一致

  • context_window varies: 1000000, 128000, 64000
  • release_date varies (span 315d): 2025-01-20, 2025-12-01

各服务商对此模型的报告值存在差异。上方「核心数据」使用代表性服务商的值;逐项请以下表为准。

Frequently asked questions

How much does DeepSeek Reasoner cost?

DeepSeek Reasoner costs $0.140 per 1M input tokens and $0.280 per 1M output tokens, sourced from deepseek. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of DeepSeek Reasoner?

DeepSeek Reasoner has a context window of 1M tokens, with a max output of 384K tokens per reply. This is the total combined size of prompt + completion.

Does DeepSeek Reasoner support tool calling?

Yes. DeepSeek Reasoner supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does DeepSeek Reasoner support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for DeepSeek Reasoner in our data source. Verify with DeepSeek's official documentation before relying on it in production.

Can DeepSeek Reasoner accept image input?

No. DeepSeek Reasoner only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is DeepSeek Reasoner open-weight?

Yes. DeepSeek Reasoner's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to DeepSeek Reasoner?

If DeepSeek Reasoner doesn't fit, consider DeepSeek-V3.2, DeepSeek V4 Pro, DeepSeek-R1-0528. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

More DeepSeek models

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Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.