AI 模型情報

DeepSeek-V3.1

deepseek/v3-1

出品方: DeepSeek · 系列: deepseek · 發布 2025-08-21 · 知識截止: 2024-07

$0.200
輸入 / 1M token
$0.700
輸出 / 1M token
131K
上下文長度
131K
最大輸出

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

能力清單

工具呼叫推理? 結構化輸出附件開放權重溫度可調
支援模態: 輸入 text · 輸出 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.

Coding62
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)2/20
  • Provider availability10/10
Agents75
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability10/10
JSON / structured output48
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume18/20
Cost efficiency64
  • Headline price (log-scaled)64/95
  • Has prompt-cache pricing0/5
Long context46
  • Context window (100K → 2M)36/90
  • Has published price for full window10/10
Production-readiness94
  • Number of independent providers40/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers4/10
  • 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
$1.35
< $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
$2.70
< $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
$0.75
< $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
$2.30
< $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
$2.82
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定價詳情

推薦定價來自 nano-gpt · deepseek-ai/DeepSeek-V3.1

$0.200
輸入
$0.700
輸出

於 18 家供應商可用

服務商服務商模型 ID輸入 / 1M輸出 / 1M上下文發布日期
Azure
azure
deepseek-v3.1$0.560$1.68131K2025-08-21
Vercel AI Gateway
vercel
deepseek/deepseek-v3.1$0.300$1.00164K2025-08-21
Together AI
togetherai
deepseek-ai/DeepSeek-V3-1$0.600$1.70131K2025-08-21
NanoGPT
nano-gpt
TEE/deepseek-v3.1$1.00$2.50164K2025-08-21
NanoGPT
nano-gpt
deepseek-ai/DeepSeek-V3.1$0.200$0.700128K2025-07-26
Abacus
abacus
deepseek/deepseek-v3.1$0.550$1.66128K2025-01-20
submodel
submodel
deepseek-ai/DeepSeek-V3.1$0.200$0.80075K2025-08-23
Alibaba (China)
alibaba-cn
deepseek-v3-1$0.574$1.72131K2025-01-01
Jiekou.AI
jiekou
deepseek/deepseek-v3.1$0.270$1.00164K2026-01
NovitaAI
novita-ai
deepseek/deepseek-v3.1$0.270$1.00131K2025-08-21
Weights & Biases
wandb
deepseek-ai/DeepSeek-V3.1$0.550$1.65161K2025-08-21
Qiniu
qiniu-ai
deepseek-v3.1UnknownUnknown128K2025-08-19
Baseten
baseten
deepseek-ai/DeepSeek-V3.1$0.500$1.50164K2025-08-25
Azure Cognitive Services
azure-cognitive-services
deepseek-v3.1$0.560$1.68131K2025-08-21
Meganova
meganova
deepseek-ai/DeepSeek-V3.1$0.270$1.00164K2025-08-25
Synthetic
synthetic
hf:deepseek-ai/DeepSeek-V3.1$0.560$1.68128K2025-08-21
SiliconFlow
siliconflow
deepseek-ai/DeepSeek-V3.1$0.270$1.00164K2025-08-25
LLM Gateway
llmgateway
deepseek-v3.1$0.560$1.68128K2025-08-21

各渠道資料存在不一致

  • context_window varies: 128000, 131072, 161000, 163840, 164000, 75000
  • release_date varies (span 365d): 2025-01-01, 2025-01-20, 2025-07-26, 2025-08-19, 2025-08-21, 2025-08-23, 2025-08-25, 2026-01
  • modalities varies across offerings

各服務商對此模型的回報值不一致。上方「核心數據」採用代表性服務商的值;逐項請以下表為準。

Frequently asked questions

How much does DeepSeek-V3.1 cost?

DeepSeek-V3.1 costs $0.200 per 1M input tokens and $0.700 per 1M output tokens, sourced from nano-gpt. 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-V3.1?

DeepSeek-V3.1 has a context window of 131K tokens, with a max output of 131K tokens per reply. This is the total combined size of prompt + completion.

Does DeepSeek-V3.1 support tool calling?

Yes. DeepSeek-V3.1 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-V3.1 support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for DeepSeek-V3.1 in our data source. Verify with DeepSeek's official documentation before relying on it in production.

Can DeepSeek-V3.1 accept image input?

No. DeepSeek-V3.1 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is DeepSeek-V3.1 open-weight?

Yes. DeepSeek-V3.1'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-V3.1?

If DeepSeek-V3.1 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

Capability lists this model is in

最近更新:

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.