
Cohere
on Orq.ai
Use Cohere’s Command family through a single Orq.ai API. Route models such as Command, Command R, and lighter Command variants via Orq’s AI Router for chat, reasoning, coding, and retrieval‑augmented workloads.
Capabilities:
Chat
Embeddings
Reasoning
Vision
Models Supported:
c4ai-aya-expanse-32b
c4ai-aya-vision-32b
command-r7b-arabic-02-2025
rerank-v4.0-fast
rerank-v4.0-pro
Provider HQ:
Cohere, headquartered in Toronto, Canada, with additional offices in London, San Francisco, New York, and Montréal.
Access Cohere through Orq.ai’s AI Router
Cohere is an enterprise AI company focused on secure, private, and customizable LLMs for businesses, offering the Command family for generation, plus Rerank and Embed models for retrieval and search. These models cover high‑end reasoning, general‑purpose coding, and cost‑efficient high‑volume tasks.
Orq.ai supports major Cohere variants (for example Command, Command R, and Command R7b), with availability depending on provider access, region, and your workspace configuration.
Cohere models available on Orq.ai
Model | Type | Context / scope | Best for | Pricing tier |
|---|---|---|---|---|
Command (full Command text / Command A‑class) | Chat / reasoning / coding | Typically 128K–256K tokens (check Cohere / Orq docs for current limits) | Complex reasoning, analysis, coding, and high‑stakes tasks where you want Cohere’s strongest general‑purpose Command model | Premium – Cohere standard API pricing; current Command‑class models are around 1.00 USD / 1M input tokens and 2.00 USD / 1M output tokens for text, with higher tiers for advanced variants |
Command R | Chat / reasoning / RAG | Up to 128K tokens (verify in Cohere / Orq docs) | Everyday production workloads, retrieval‑augmented generation, coding, product features, and workflows that balance quality with cost and latency | Mid‑tier – Command R pricing around 0.15 USD / 1M input tokens and 0.60 USD / 1M output tokens (cache‑miss rates), making it a strong option |
Command R7b / Command Light | Chat / fast / cost‑efficient | Up to 128K tokens (confirm per model), smaller parameter count | Fast, lower‑cost tasks such as classification, extraction, lightweight chat, routing, and high‑volume support workflows where 7B‑class models are enough | Cost‑efficient – Command Light and Command R7b models can be as low as ~0.03–0.30 USD / 1M input tokens and ~0.15–0.60 USD / 1M output tokens depending on the specific variant |
Pricing tiers here are approximate and based on Cohere’s public Command family pricing; Orq.ai may apply its own billing or BYOK mapping. Always check Orq.ai’s pricing page and your configured Cohere provider for current per‑model rates, quotas, and billing details.
Why use Cohere through Orq.ai?
Capability | Provider / models | Direct | Through Orq.ai |
|---|---|---|---|
Chat | Cohere Command family (Command, Command R, Command Light/R7b) | Call Command models directly via Cohere’s API for chat, reasoning, coding, and RAG use cases | Use Cohere models through Orq.ai’s OpenAI‑compatible endpoint, adding routing, tracing, evals, budgets, and governance controls around each request |
Code | Command / Command R models tuned or suitable for coding | Use Cohere directly for code generation, debugging, refactoring, and agentic coding workflows | Route coding workloads through Orq.ai, compare Cohere Command models against other providers, and monitor cost, latency, and quality from one control layer |
Embeddings & rerank | Embed and Rerank models configured in Orq.ai | Cohere offers specialized Embed and Rerank models for search, ranking, and retrieval | Use Orq.ai to route embedding and rerank workloads to those specialized models while keeping Command/Command R for reasoning, generation, and agent steps |
This gives teams a practical way to use Cohere 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 | Cohere model pricing may differ depending on whether you: | * connect your own Cohere account and API key (BYOK), or | * use Cohere 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 Cohere models through:
an OpenAI‑compatible API layer, and
native SDKs and router integrations where applicable
That means:
Popular AI frameworks (for example, OpenAI‑compatible clients, LangChain‑style frameworks, and orchestration libraries) can talk to Cohere via Orq’s router.
Code assistants and IDE tools that support MCP or OpenAI‑compatible APIs (Cursor, VS Code, Claude Desktop, Warp, Zed, TRAE, and similar tools you’ve documented) can route through Orq.ai to Cohere, depending on model and integration configuration.
Check the Orq.ai integration docs for the latest supported frameworks and tools for Cohere.
FAQs
Do I need a separate Cohere account to use Cohere through Orq.ai?
You can either connect your own Cohere API key into Orq.ai or, where available, use Cohere models billed via Orq.ai; the exact options depend on your Orq plan, region, and how Cohere is configured in your workspace. In both cases, Orq.ai gives you one place to manage routing, observability, and cost controls around that Cohere usage.
Can I route only some workflows to Cohere and others to different providers?
Yes. You define routes per workflow in Orq.ai and decide which ones should use Cohere vs other providers, so you can reserve Command/Command R for specific RAG, enterprise, or compliance‑sensitive workloads while sending other tasks to different models.
Does using Cohere 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.
Alternatives to
Cohere
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
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Chat
Code
Image Generation
Reasoning
Speech
Vision
Models:
gpt-5.5 (EU)
gpt-5.6-luna (EU)
gpt-5.6-sol (EU)
Google AI
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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
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Chat
Code
Embeddings
Reasoning
Vision
Models:
eu.anthropic.claude-opus-5
global.anthropic.claude-opus-5
us.anthropic.claude-opus-5


