DeepSeek

DeepSeek-R1 Distill Qwen 32B

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
Modelo de Pesos AbertosOfficial Source Verified ↗
46
Intelligence Index

O DeepSeek-R1 Distill Qwen 32B da DeepSeek é um modelo de inteligência artificial com janela de contexto de 131K tokens e preço de API de $0.2/1M na entrada e $0.6/1M na saída, projetado para programação, raciocínio e automação empresarial.

Technical Specifications

Provider
DeepSeek
Category
reasoning
Release Date
2025-01
Knowledge Cutoff
July 2024
Architecture
Dense Distilled Reasoning Transformer
Parameters
32B
Context Window
131K tokens
Max Output
8K tokens
Cached Input Price
$0.02 / 1M tokens
Batch API Discount
50% off async batch
Consumer Subscription
Free / Self-Hosted
Reasoning Mode
Yes (Chain-of-Thought)
Reasoning Effort Control
Configurable (Low / Med / High)
Tool Calling
Yes
Structured Outputs
Yes
Open Weights
Yes (Open Source / Self-Hostable)
Input Modalities
text
Output Modalities
text
Official Documentation
Visit Official Docs ↗

Data Privacy, Licensing & Deployment Governance

API Data Training Policy
100% Isolated when self-hosted on private GPUs or VPC
Model License & Commercial Rights
Permissive Open-Weights (Apache 2.0 / MIT Commercial)
Deployment & Cloud Availability
Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API
Output Ownership
Full commercial ownership of generated outputs

Official Provider Release Intelligence, API Quotas & Agentic Specs

Compare Multi-Models Side-by-Side →
Official API Model ID (SDK String)
deepseek-reasoner
Supported SDK & API Protocol
OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Lifecycle & Deprecation Status
Active GA (Guaranteed support through 2027+)
Production Rate Limits (RPM & TPM)
Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Pricing Tier (>128K / >200K)
Flat rate ($0.2/1M in) across full 131K window
Prompt Cache Write & TTL Policy
Automatic prefix caching at $0.02/1M (no extra cache-write fee)
Computer Use & Browser GUI Agent
API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool Calling
Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Code Sandbox
Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Fine-Tuning & Distillation Support
Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Tokenization Billing
Text BPE (~4 chars/token)
Weights Precision & Quantization
BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0)
Minimum GPU VRAM Requirement
20 GB VRAM (4-bit Quantized) · 69 GB VRAM (Native BF16)
Supported Inference Engines
vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI
System Card & Safety Framework
Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (SOC2 / HIPAA / ZDR)
100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Engineering & Pricing Workbench

DeepSeek-R1 Distill Qwen 32B Cost, Context, Hardware & API Integration

500 / day
4,000 tok
1,000 tok
Conversation Depth (History Re-billing):1 Turn (Single-Shot)
50%
Estimated Monthly API Cost (30 Days)
$15.60$21.00
Monthly Savings: $5.40 (Caching/Batch)
Subscription ($20/mo) vs API

Pay-as-you-go API is cheaper for this volume (saves $4.40/mo vs $20 flat plan).

Break-even point: ~641 requests/day equals $20/month.

Same Monthly Workload Cost Across Popular Reference Models

DeepSeek-R1 Distill Qwen 32B (Active)
$15.60
/ month
Gemini 2.5 Flash
$18.00
/ month
DeepSeek V3
$32.70
/ month
GPT-4o
$300.00
/ month
Claude 3.7 Sonnet
$405.00
/ month

Live Prompt Paste Tokenizer & Cost Counter

Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.

Chars / Words
175 / 24
OpenAI o200k
~46 tok
Claude BPE
~49 tok
Llama / DeepSeek
~51 tok

Hybrid Prompt Routing Cascade Simulator

Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to DeepSeek-R1 Distill Qwen 32B:

Cascaded Monthly Bill:$17.40/mo
This model is already priced at or below the fast router baseline.

Benchmark Scores & 6-Axis Capability Radar

Benchmark Encyclopedia
Coding (59)Reasoning (76)Knowledge (75)Speed (39)Context (75)Cost Value (94)
DeepSeek-R1 Distill Qwen 32B2026 Frontier Median
SWE-bench Verified
51.2%
GPQA Diamond
65.9%
MMLU-Pro
75.3%
HumanEval
92.8%
Humanity's Last Exam
9.4%
Terminal-Bench
31%
SciCode
37.1%
LiveCodeBench
57.2%
AIME
72.6%
Long-Context Reasoning
68.4%
Chatbot Arena Elo
1308pts

Strengths

  • Arquitetura Dense Distilled Reasoning Transformer avançada da DeepSeek com contexto de 131K tokens
  • Excelente relação custo-benefício ($0.2/1M entrada, $0.6/1M saída) e baixa latência
  • Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues

Limitations & Trade-offs

  • Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
  • Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos

Editorial Assessment

O DeepSeek-R1 Distill Qwen 32B da DeepSeek oferece um equilíbrio sólido entre inteligência, velocidade e eficiência de custos.

Best for: Automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com DeepSeek

Frequently Asked Questions about DeepSeek-R1 Distill Qwen 32B

How much does the DeepSeek-R1 Distill Qwen 32B API cost per 1M tokens?+

DeepSeek-R1 Distill Qwen 32B by DeepSeek is priced at $0.2 per 1M input tokens and $0.6 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.02 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.

Should I use a $20/month subscription or the DeepSeek-R1 Distill Qwen 32B pay-as-you-go API?+

A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.

How many words and pages fit in DeepSeek-R1 Distill Qwen 32B's context window?+

DeepSeek-R1 Distill Qwen 32B features a 131K tokens context window, which equals approximately 98,304 English words or ~262 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.

Can I run DeepSeek-R1 Distill Qwen 32B locally on my own GPU (Open Weights)?+

Yes, DeepSeek-R1 Distill Qwen 32B (32B) releases open weights that can be self-hosted locally or on private cloud GPUs using vLLM, Ollama, SGLang, or llama.cpp.

Does DeepSeek train on data sent to the DeepSeek-R1 Distill Qwen 32B API, and is commercial use allowed?+

100% Isolated when self-hosted on private GPUs or VPC. License tier: Permissive Open-Weights (Apache 2.0 / MIT Commercial). Full commercial ownership of generated outputs. Supported deployment channels include: Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API.

How does DeepSeek-R1 Distill Qwen 32B perform on coding and reasoning benchmarks?+

DeepSeek-R1 Distill Qwen 32B achieves a composite Intelligence Index of 46/100, scoring 51.2% on SWE-bench Verified, 65.9% on GPQA Diamond, 75.3% on MMLU-Pro, and 1308 pts on Chatbot Arena Elo.

What is DeepSeek-R1 Distill Qwen 32B best used for?+

DeepSeek-R1 Distill Qwen 32B is best suited for: Automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com DeepSeek. Assessment: O DeepSeek-R1 Distill Qwen 32B da DeepSeek oferece um equilíbrio sólido entre inteligência, velocidade e eficiência de custos.

AI Glossary & Architecture Concepts

View full glossary →

Key machine learning concepts and benchmarks relevant to DeepSeek-R1 Distill Qwen 32B:

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fontes oficiais: DeepSeek-R1 Official Technical Report↗