763B total / 16B activo causal encoder-decoder MoE con 1/4 KV-cache usage, nativo visión, MIT license, y mundo-record bajo off-pico precios.
Technical Specifications
- Provider
- DeepSeek
- Category
- open-source
- Release Date
- 2026-09
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- Free / Self-Hosted
- Reasoning Effort Control
- Configurable (Low / Med / High)
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- 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 2028+)
- 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 ($0.3/1M in) across full 1000K window
- Prompt Cache Write & TTL Policy
- Automatic prefix caching at $0.006/1M (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) · Vision (~258–765 tokens per image tile)
- Weights Precision & Quantization
- BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0)
- Minimum GPU VRAM Requirement
- 473 GB VRAM (4-bit Quantized) · 1640 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
DeepSeek V4.1-Flash Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~368 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to DeepSeek V4.1-Flash:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 74.2%
- GPQA Diamond
- 90.9%
- MMLU-Pro
- 89.5%
- HumanEval
- 96.5%
- Humanity's Last Exam
- 16.8%
- Terminal-Bench
- 31.2%
- SciCode
- 48%
- LiveCodeBench
- 73%
- AIME
- 92.4%
- Long-Context Reasoning
- 93%
- Chatbot Arena Elo
- 1455pts
Strengths
- MIT permissive abierto license con completo weights, arquitectura, y code
- Revolutionary causal encoder-decoder arquitectura: KV cache solo 890 bytes/token (se ejecuta en commodity NVMe SSDs)
- de mundo más bajo precios: off-pico cached entrada un just $0.003/1M y $0.27 costo por benchmark tarea
- Colossal 1M contexto entrada paired con 384,000 maximum salida tokens y nativo visión
Limitations & Trade-offs
- Extremely verbose generación (averages 8.9K salida tokens por inquiry sin explicit caps)
- de largo alcance rendimiento degrades en Terminal-Bench 4.0 (31.2%)
- Factual knowledge recall dips en SimpleQA (42.3) y visión resolución es capped un 672x672
- Highly sensitive un agente harness prompts y system prompt engineering
Editorial Assessment
un architectural tour-de-force que destroys KV-cache bottlenecks y sets un todos-tiempo bajo precio ceiling para abierto de frontera AI.
Best for: Extreme económico batch procesamiento, autohospedado commodity hardware clústeres, y masivo de formato largo razonamiento tareas
Compare DeepSeek V4.1-Flash
Frequently Asked Questions about DeepSeek V4.1-Flash
How much does the DeepSeek V4.1-Flash API cost per 1M tokens?+
DeepSeek V4.1-Flash by DeepSeek is priced at $0.3 per 1M input tokens and $1.2 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.006 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the DeepSeek V4.1-Flash 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 V4.1-Flash's context window?+
DeepSeek V4.1-Flash features a 1M tokens context window, which equals approximately 750,000 English words or ~2,000 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 384,000 tokens.
Can I run DeepSeek V4.1-Flash locally on my own GPU (Open Weights)?+
Yes, DeepSeek V4.1-Flash (763B total (8B prefill / 16B decode active)) 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 V4.1-Flash 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 V4.1-Flash perform on coding and reasoning benchmarks?+
DeepSeek V4.1-Flash achieves a composite Intelligence Index of 58/100, scoring 74.2% on SWE-bench Verified, 90.9% on GPQA Diamond, 89.5% on MMLU-Pro, and 1455 pts on Chatbot Arena Elo.
What is DeepSeek V4.1-Flash best used for?+
DeepSeek V4.1-Flash is best suited for: Extreme económico batch procesamiento, autohospedado commodity hardware clústeres, y masivo de formato largo razonamiento tareas. Assessment: un architectural tour-de-force que destroys KV-cache bottlenecks y sets un todos-tiempo bajo precio ceiling para abierto de frontera AI.
DeepSeek Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to DeepSeek's flagship reasoning tier:
DeepSeek V4 Pro
DeepSeek V4
DeepSeek Reasoner
DeepSeek Chat
DeepSeek-R1-0528
DeepSeek-V3-0324
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to DeepSeek V4.1-Flash:
La unidad básica de texto que procesa un modelo de lenguaje, que normalmente equivale a 3 o 4 caracteres o aproximadamente 0,75 palabras. Por ejemplo, una frase típica se divide en varios tokens.
Un conjunto estandarizado de pruebas para evaluar y comparar objetivamente las capacidades de distintos modelos de IA en tareas como programación (SWE-bench) o matemáticas avanzadas (AIME).
La cantidad máxima de tokens que un modelo puede considerar a la vez, incluyendo tanto la entrada que lee como la salida que genera. Una ventana de 1.000.000 de tokens puede procesar unas 750.000 palabras en una sola petición.
Un modelo de IA entrenado para invertir cómputo adicional en pensar y validar hipótesis lógicas antes de responder, diseñado para problemas complejos de ingeniería y matemáticas.
Una técnica de razonamiento paso a paso donde el modelo genera pensamientos intermedios antes de formular la respuesta final, mejorando radicalmente la resolución de problemas matemáticos y lógicos.
La capacidad de un modelo de detectar la necesidad de una función externa y emitir argumentos JSON estructurados para ejecutar API, búsquedas web o consultas a bases de datos.
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: DeepSeek V4.1-Flash Technical Report & Open Weights Release (September 2026)↗