Key facts
| Cohere API surface | Cohere-native v2 APIs plus an OpenAI compatibility endpoint; Cohere-specific parameters are not all supported there |
| Cohere pricing model | Usage-based pricing per endpoint and model; enterprise agreements for private deployments |
| Cohere deployment | Managed SaaS, cloud marketplaces and enterprise private deployments |
| Plugsky API compatibility | OpenAI-compatible /v1/chat/completions; change the base URL and model name |
| Plugsky pricing model | Flat monthly self-serve plans with unlimited fair-use usage; no per-token billing |
| Plugsky model access | 30+ chat models plus embedding models behind one API |
| Plugsky retrieval stack | Embeddings and RAG are live; no dedicated rerank endpoint yet |
| Plugsky deployment and residency | Plugsky cloud, your VPC, on-prem and air-gapped; region selection for residency |
TL;DR
- Cohere's rerank and multilingual embeddings are the parts Plugsky does not fully replace yet.
- Plugsky gives you OpenAI-compatible chat, embeddings and RAG under one flat self-serve plan.
- Generation is usually the easiest layer to migrate; retrieval needs its own eval pass.
- Free plan with 2 free AI models (plugsky-micro, plugsky-lite) plus a 14-day full-access trial.
- A hybrid split — Cohere for rerank, Plugsky for generation — is common and supported by the API shapes.
How it works, step by step
- Split your pipeline into retrieval (embed, store, rerank) and generation (chat, tools, JSON).
- Create a Plugsky account and API key on the free plan (no card required).
- Migrate the generation layer first: swap the Cohere chat client for an OpenAI-compatible client with the Plugsky base URL.
- Keep Cohere Rerank in place while you evaluate whether embedding similarity or a custom scorer is enough.
- Re-embed a sample corpus with a Plugsky embedding model and measure retrieval quality on your labelled queries.
- If quality holds, backfill the full corpus into a new collection and switch the retrieval path.
- Decommission Cohere endpoints one at a time, keeping the rerank stage until its replacement passes evaluation.
Original data
Try it yourself
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Where Cohere wins
Cohere's retrieval stack is the differentiator. Rerank is a first-class endpoint that many teams rely on to lift retrieval precision without retraining a cross-encoder themselves, and Cohere's multilingual embedding models are strong on non-English corpora. Private deployments are mature, including marketplace and on-prem options, and the platform bundles enterprise search features such as connectors and citation-oriented responses. If retrieval quality is the core of your product, these are real reasons to keep Cohere in the stack.
Where Plugsky wins
Plugsky wins on generation and consolidation. One OpenAI-compatible endpoint covers 30+ chat models, and embeddings and RAG are live on the same platform, so a knowledge assistant can be built without a second vendor. Self-serve pricing is flat monthly with unlimited fair-use usage, which removes per-call anxiety from high-volume retrieval-augmented loops. The free plan includes two free AI models and there is a 14-day full-access trial. Enterprise deployments add your VPC, on-prem and air-gapped options with region selection for residency.
What to test before switching
Treat retrieval and generation as separate migrations. For retrieval, build a labelled query set and measure recall and precision with and without rerank — this is where Cohere may still win. For generation, compare answer faithfulness on the same retrieved context, JSON adherence for structured extraction, and tool use. Check embedding dimensions and normalisation before re-embedding: changing dimensions means rebuilding the vector index, not just swapping a client. Validate the data path end to end if your corpus is regulated.
Migration path from Cohere to Plugsky
Start with the generation layer behind an interface: a Cohere client for the legacy path and an OpenAI-compatible client with base_url='https://api.plugsky.com/v1' for Plugsky. Keep Rerank on Cohere until you have measured alternatives, then decide whether to re-embed with a Plugsky embedding model and re-rank with similarity plus your own scoring. Because Cohere also exposes an OpenAI compatibility endpoint, you can point your existing OpenAI-style code at either provider during evaluation and move one stage at a time.
Honest comparison
| Capability | Plugsky | Cohere | Building in-house |
|---|---|---|---|
| API compatibility | OpenAI-compatible chat completions | Cohere v2 APIs plus OpenAI compatibility endpoint | Full rewrite |
| Pricing model | Flat monthly self-serve, unlimited fair use | Usage-based per endpoint and model | GPU + ops cost |
| Chat model access | 30+ models, one API | Command family | You host each model |
| Embeddings | Live, multiple embedding models | Strong multilingual embedding models | You host |
| Rerank | No dedicated rerank endpoint yet — keep Cohere or build your own | Native Rerank API | You build it |
| Deployment and residency | Cloud, VPC, on-prem, air-gapped | SaaS plus enterprise private deployments | You control |
Frequently asked questions
Can I use the OpenAI SDK with Plugsky instead of Cohere?
Yes. Plugsky exposes an OpenAI-compatible chat completions endpoint. Cohere also offers a compatibility endpoint, so OpenAI-style code can be pointed at either provider during evaluation.
Does Plugsky replace Cohere Rerank?
Not today. Plugsky does not offer a dedicated rerank endpoint, so pipelines that depend on Rerank should keep Cohere for that stage or implement their own scoring.
How does Plugsky pricing differ from Cohere?
Cohere bills per endpoint and model usage. Plugsky self-serve plans are flat monthly with unlimited fair-use usage and no per-token charges. See the live pricing page for current plans.
Can I migrate embeddings without rebuilding my index?
Only if dimensions and preprocessing match. In practice, plan to re-embed into a new collection and backfill, then switch the retrieval path after an eval.
Does Plugsky support RAG and agents?
Yes — embeddings, RAG and agents are live on Plugsky, so you can build a knowledge assistant on the same platform as your chat traffic.
Can I run Cohere and Plugsky side by side?
Yes. Keep Cohere for retrieval or rerank and use Plugsky for generation, then expand the Plugsky share as your evaluations justify it.
What about private deployment?
Both platforms support private options. Plugsky adds VPC, on-prem and air-gapped deployments with region selection for enterprise customers.
Is there a free way to evaluate Plugsky?
Yes. The free plan includes two free AI models with no card required, and a 14-day full-access trial is available.