Models

What is plugsky-mistral-medium and when should you use it?

plugsky-mistral-medium is the Mistral-family profile in Plugsky's 30+ model catalogue, built for long-context chat and general work. It supports streaming, function calling, JSON mode and long inputs on the OpenAI-compatible API. Choose it when your organisation standardises on Mistral-facing models or you want a Mistral-style alternative; check /models for the live window, latency and routing before committing.

Key facts

Model classMistral-family profile in the Plugsky catalogue
Best forLong-context chat, general work and Mistral-standardised pipelines
Context class128K-class window; live limits are published per model
CapabilitiesStreaming, function calling, JSON mode and long-context inputs
Pricing tierPaid-plan model; free plan covers plugsky-micro and plugsky-lite
APIOpenAI-compatible /v1/chat/completions — keep your SDK
AvailabilityRouted with same-profile fallback; live upstream is shown at /models
Product statusLive

TL;DR

  • A Mistral-family profile for teams with Mistral-facing standards.
  • Long-context chat and general work on the OpenAI-compatible API.
  • Latency can vary by routing — measure before putting it on a hot path.
  • Compare with plugsky-kimi and plugsky-longctx for long-prompt workloads.
  • Same-profile fallback keeps the profile available during incidents.

How it works, step by step

  1. Read the live card at /models for the current window, features and serving engine.
  2. Measure latency on representative prompts before using it in a hot path.
  3. Test quality on your main workloads: chat, extraction and long inputs.
  4. Compare against plugsky-kimi and plugsky-longctx on long-prompt tasks.
  5. Switch the model name and keep a faster default for latency-sensitive routes.
  6. Monitor routing changes at /models so results stay interpretable.
  7. Re-run your evaluation after catalogue updates.
1Read the live cardat /models for thecurrent window,2Measure latency onrepresentativeprompts before3Test quality onyour mainworkloads: chat,4Compare againstplugsky-kimi andplugsky-longctx on5Switch the modelname and keep afaster default for6Monitor routingchanges at /modelsso results stay

Try it yourself

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What plugsky-mistral-medium is

plugsky-mistral-medium is the Mistral-family profile in the Plugsky catalogue. It exists for two audiences: teams whose tooling, skills or standards already centre on Mistral models, and teams that want a Mistral-style alternative behind the same OpenAI-compatible API as the rest of the catalogue. It handles long-context chat and general work with streaming, function calling and JSON mode.

Latency and the engine serving the profile can vary as platform routing changes, so the live card at /models is the page to check before putting it on a latency-sensitive path.

When to choose it

Choose plugsky-mistral-medium when Mistral compatibility is a requirement — for example, prompt libraries or evaluations built around Mistral behaviour — or when you want a long-context chat model with an independent lineage from the rest of your stack. It is also a reasonable general-purpose option for chat and extraction work.

For long-document synthesis, compare with plugsky-kimi and plugsky-longctx. For everyday production traffic with tighter latency expectations, a workhorse model such as plugsky-pro may be the better default.

Latency, routing and cost trade-offs

Family profiles are route-served: they are kept available by falling back to same-profile capacity. That is good for uptime, but it means latency and exact model identity can change, so measure rather than assume.

  • Keep it off the hottest path unless your measurements support it.
  • Record model metadata in responses so routing changes are visible.
  • Use JSON mode with validation for structured workloads.
  • Run a small regression suite after catalogue updates.
  • Self-serve plans are flat monthly with fair-use usage — see the live pricing page for current plans.

How to switch to plugsky-mistral-medium

Switching is one model name on the OpenAI-compatible endpoint: {"model": "plugsky-mistral-medium", "messages": [{"role": "user", "content": "Summarise this 60-page report and list the decisions."}]}.

Shadow-test against your current model, check latency percentiles on real prompts, then route the workload slice it wins. Keep a faster model as the default for interactive routes.

Honest comparison

Dimensionplugsky-mistral-mediumplugsky-kimiplugsky-pro
Best fitMistral-standardised teams and long-context chatCross-document synthesis and bilingual workEveryday production workhorse
FamilyMistral profileLong-context profilePlatform default profile
Latency profileCan vary with routing — measure itBalancedBalanced
Tools and JSON modeSupportedSupportedSupported
Context class128K-class128K-class128K-class
FailoverAutomatic same-profile fallbackAutomatic same-profile fallbackAutomatic peer fallback

Frequently asked questions

Is plugsky-mistral-medium free?

No — it is a paid-plan model. The free plan includes two free models, plugsky-micro and plugsky-lite. A 14-day full-access trial is available for paid tiers.

What context window does it have?

It is 128K-class today. The exact live window and output limit are published per model at /models.

Why does latency vary?

Family profiles are kept available through routing, which can move between engines. Measure on your own prompts and treat /models as the source of truth for what is serving the model.

Does it support tools and structured output?

Yes — streaming, function calling and JSON mode are part of the shared OpenAI-compatible surface.

How is it different from other long-context models?

It carries a Mistral-family lineage and profile. Compare it with plugsky-kimi and plugsky-longctx on the same documents and choose on measured results.

Should I use it for a latency-sensitive app?

Only after measuring. If response time is critical, use a measured-fast model as the default and route long-context or Mistral-specific work to this profile.

How do I migrate from the Mistral API?

Change the base URL to the Plugsky endpoint and set the model name. Because the endpoint is OpenAI-compatible, you may also simplify to an OpenAI-style client.

How is pricing structured?

Self-serve plans are flat monthly with fair-use usage and no per-token billing. See the live pricing page for current plans.