élevé-efficacité 1M-contexte instruction-tuned conversation modèle based sur le DeepSeek V3.2 core, offrant extreme prix disruption.
Technical Specifications
- Provider
- DeepSeek
- Category
- open-source
- Release Date
- 2025-12
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- Free / Self-Hosted
- Reasoning Effort Control
- Fixed
- 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-chat
- 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 ($0.28/1M in) across full 1000K window
- Prompt Cache Write & TTL Policy
- Automatic prefix caching at $0.028/1M (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
- 416 GB VRAM (4-bit Quantized) · 1443 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 Chat Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $4.46/mo vs $20 flat plan).
Break-even point: ~644 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 Chat:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 54%
- GPQA Diamond
- 65%
- MMLU-Pro
- 79.5%
- HumanEval
- 92%
- Humanity's Last Exam
- 10.8%
- Terminal-Bench
- 36%
- SciCode
- 33.5%
- LiveCodeBench
- 56.5%
- AIME
- 74%
- Long-Context Reasoning
- 82.5%
- Chatbot Arena Elo
- 1335pts
Strengths
- Groundbreaking 1M fenêtre de contexte à un astonishing $0.28 dans / $0.42 out par millions tokens
- Multi-Head Latent Attention (MLA) architecture drastically reduces KV-cache mémoire overhead
- à poids ouverts availability pour customized d'entreprise déploiement
Limitations & Trade-offs
- texte-seulement modèle sans natif visuel ou audio compréhension
- manque de profond multi-étapes raisonnement pour compétitif mathematics
Editorial Assessment
un extraordinary prix-performances jalon qui makes millions-token instruction following accessible à everyone.
Best for: ultra-faible-coût conversationnel agents, grand document querying, et automatisé client support
Compare DeepSeek Chat
Frequently Asked Questions about DeepSeek Chat
How much does the DeepSeek Chat API cost per 1M tokens?+
DeepSeek Chat by DeepSeek is priced at $0.28 per 1M input tokens and $0.42 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.028 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the DeepSeek Chat 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 Chat's context window?+
DeepSeek Chat 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 16,384 tokens.
Can I run DeepSeek Chat locally on my own GPU (Open Weights)?+
Yes, DeepSeek Chat (671B Total (37B 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 Chat 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 Chat perform on coding and reasoning benchmarks?+
DeepSeek Chat achieves a composite Intelligence Index of 50/100, scoring 54% on SWE-bench Verified, 65% on GPQA Diamond, 79.5% on MMLU-Pro, and 1335 pts on Chatbot Arena Elo.
What is DeepSeek Chat best used for?+
DeepSeek Chat is best suited for: ultra-faible-coût conversationnel agents, grand document querying, et automatisé client support. Assessment: un extraordinary prix-performances jalon qui makes millions-token instruction following accessible à everyone.
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 V4.1-Flash
DeepSeek V4 Pro
DeepSeek V4
DeepSeek Reasoner
DeepSeek-R1-0528
DeepSeek-V3-0324
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to DeepSeek Chat:
L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.
Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).
Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.
La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.
Un standard ouvert créé par Anthropic permettant aux agents d'IA de se connecter de façon uniforme aux systèmes de fichiers locaux, aux environnements de développement et aux API tierces.
Une optimisation tarifaire et technique conservant les états d'attention des préfixes de prompts récurrents, réduisant les coûts d'entrée de 50 à 90 % tout en abaissant la latence.
Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: DeepSeek Official Pricing & Platform Updates (Late 2025)↗