DeepSeek
on Orq.ai
Use DeepSeek’s LLMs through a single Orq.ai API. Route models such as DeepSeek V‑series (for example V3/V4) and DeepSeek R‑series (reasoning models) via Orq’s AI Router for chat, reasoning, coding, and high‑volume workloads.
Capabilities:
Chat
Reasoning
Models Supported:
deepseek-v4-flash
deepseek-v4-pro
deepseek-chat
deepseek-reasoner
Provider HQ:
DeepSeek, headquartered in Hangzhou, Zhejiang, China.
Access DeepSeek through Orq.ai’s AI Router
DeepSeek is a provider of cost‑efficient, high‑performance LLMs delivered via an OpenAI‑compatible API, with models such as DeepSeek‑V3 and DeepSeek‑R1 designed to undercut incumbents on price while maintaining strong benchmarks. These models cover complex reasoning, general‑purpose coding, and extremely cost‑efficient high‑volume use cases.
Orq.ai supports major DeepSeek variants (for example DeepSeek‑V3/V4‑class chat models and DeepSeek‑R1 reasoning models), with availability depending on provider access, region, and your workspace configuration.
DeepSeek models available on Orq.ai
Model | Type | Context / scope | Best for | Pricing tier |
|---|---|---|---|---|
DeepSeek‑R1 (reasoning model) | Chat / reasoning / “thinking” | Typically around 128K tokens (check DeepSeek / Orq docs for current limits) | Complex reasoning, chain‑of‑thought‑style “thinking” tasks, advanced analysis, and high‑stakes workflows that need DeepSeek’s strongest reasoning model | Premium – around 0.55 USD / 1M input tokens and 2.19 USD / 1M output tokens for DeepSeek‑R1, positioned as a low‑cost but capable reasoning model vs peers |
DeepSeek‑V3 / V4 (chat / general LLM) | Chat / reasoning / coding | Often 128K–164K context (verify in DeepSeek / Orq docs) | Everyday production workloads, RAG, coding, product features, and workflows that balance quality with extremely low cost | Mid‑tier – DeepSeek‑V3 pricing as low as 0.14 USD / 1M input and 0.28 USD / 1M output tokens; some V4 tiers reported around 0.435 USD / 1M input and 0.87 USD / 1M output for flagship models |
DeepSeek V “Flash” / smaller fast models | Chat / fast / cost‑efficient | Medium–large context (confirm in docs; some V4 Flash tiers up to 1M context) | Fast, very low‑cost tasks such as classification, extraction, lightweight chat, routing, and high‑volume support workflows | Cost‑efficient – some DeepSeek V‑series Flash tiers priced under 0.10 USD / 1M input tokens and 0.20 USD / 1M output tokens, with heavy discounts on cache hits |
Pricing tiers here are approximate and based on DeepSeek’s public API pricing; Orq.ai may apply its own billing or BYOK mapping. Always check Orq.ai’s pricing page and your configured DeepSeek provider for current per‑model rates, quotas, and billing details.
Why use DeepSeek through Orq.ai?
Capability | Provider / models | Direct | Through Orq.ai |
|---|---|---|---|
Chat | DeepSeek V‑series (for example V3, V4, V3.2) | Call DeepSeek’s chat models directly via their OpenAI‑compatible API for chat, reasoning, coding, and RAG | Use DeepSeek models through Orq.ai’s OpenAI‑compatible endpoint, adding routing, tracing, evals, budgets, and governance controls around each request |
Code | DeepSeek V / R models suitable for coding/analysis | Use DeepSeek directly for code generation, debugging, refactoring, and agentic coding workflows at very low token prices | Route coding workloads through Orq.ai, compare DeepSeek models against other providers, and monitor cost, latency, and quality from one control layer |
Embeddings | Embedding providers configured in Orq.ai | DeepSeek focuses primarily on chat/reasoning; embeddings may be handled by separate models or providers | Use Orq.ai to route embedding workloads to supported embedding providers while keeping DeepSeek for reasoning, generation, and agent steps |
This gives teams a practical way to use DeepSeek where it performs best while centralising routing, observability, evals, and cost controls across the wider model stack.
Pricing
Tier / model | Input / price | Output / included | Cached / notes |
|---|---|---|---|
Model rates | DeepSeek model pricing may differ depending on whether you: | * connect your own DeepSeek account and API key (BYOK) using their OpenAI‑compatible endpoint, or | * use DeepSeek models billed through Orq.ai where available Check the Orq.ai pricing page and your workspace’s provider configuration for current per‑model rates, quotas, and plan details. |
Compatible frameworks and tools
Orq.ai exposes DeepSeek models through:
an OpenAI‑compatible API layer (DeepSeek’s native interface is OpenAI‑style), and
router integrations where applicable
That means:
Popular AI frameworks (for example, OpenAI‑compatible clients, AI SDKs, and orchestration libraries) can talk to DeepSeek via Orq’s router simply by pointing to Orq’s OpenAI‑compatible endpoint
Code assistants and IDE tools that support MCP or OpenAI‑compatible APIs (Cursor, VS Code, Claude Desktop, Warp, Zed, TRAE, and similar tools) can route through Orq.ai to DeepSeek, depending on model and integration configuration
Check the Orq.ai integration docs for the latest supported frameworks and tools for DeepSeek.
FAQs
Do I need a separate DeepSeek account to use DeepSeek through Orq.ai?
You can either connect your own DeepSeek API key into Orq.ai (using DeepSeek’s OpenAI‑compatible base URL) or, where available, use DeepSeek models billed via Orq.ai; the exact options depend on your Orq plan, region, and how DeepSeek is configured in your workspace. In both cases, Orq.ai gives you one place to manage routing, observability, and cost controls around that DeepSeek usage.
Can I route only some workflows to DeepSeek and others to different providers?
Yes. You define routes per workflow in Orq.ai and decide which ones should use DeepSeek vs other models, so you can reserve DeepSeek for price‑sensitive, high‑volume, or certain regional workloads while sending other tasks to different providers.
Does using DeepSeek through Orq.ai add latency?
Orq.ai is designed as a lightweight router layer, so the added overhead is small compared to the model’s own latency. You can use routing policies, caching, and provider selection to keep end‑to‑end performance within your targets while leveraging DeepSeek’s cost and throughput advantages.
Alternatives to
DeepSeek
Anthropic
Use Claude Opus 4.7, Sonnet 4.6, Haiku 4.5, and other supported Claude models through one API.
Chat
Code
Reasoning
Vision
Models:
claude-opus-5
claude-sonnet-5
claude-fable-5
Open AI
Use OpenAI's foundation models through a single Orq.ai API. Route models such as GPT-4.1, GPT-4.1-mini, o3-mini, and GPT-4o-class models via Orq's AI Router for chat, reasoning, coding, and multimodal workloads.
Chat
Code
Image Generation
Reasoning
Speech
Vision
Models:
gpt-5.5 (EU)
gpt-5.6-luna (EU)
gpt-5.6-sol (EU)
Google AI
Use Google’s Gemini models through a single Orq.ai API. Route models such as Gemini 3.1 Pro, Gemini 2.5 Flash, and Gemini 2.0 Flash‑Lite via Orq’s AI Router for chat, reasoning, coding, and multimodal workloads.
Chat
Code
Embeddings
Image Generation
Reasoning
Speech
Vision
Models:
gemini-3.5-flash-lite (Gemini API)
gemini-3.6-flash (Gemini API)
Gemini 3 Pro Image
AWS
Use AWS Bedrock’s foundation models through a single Orq.ai API. Route models such as Amazon Nova, Amazon Titan Text, and compatible third‑party models exposed via Bedrock through Orq’s AI Router for chat, reasoning, coding, and multimodal workloads.
Chat
Code
Embeddings
Reasoning
Vision
Models:
eu.anthropic.claude-opus-5
global.anthropic.claude-opus-5
us.anthropic.claude-opus-5
