Models

What is plugsky-reasoning and when should you use it?

plugsky-reasoning is the reasoning-first profile in Plugsky's 30+ model catalogue, aimed at problems where the model should think before answering: math, logic, planning, code analysis and multi-constraint decisions. It supports streaming, function calling, JSON mode and long-context inputs on the OpenAI-compatible API. Use it for hard single-shot questions and as an escalation target; keep faster tiers for routine traffic and check /models for the live window.

Key facts

Model classReasoning-first profile in the Plugsky catalogue
Best forMath, logic, planning, code analysis and multi-constraint decisions
Context class128K-class window; live limits are published per model
CapabilitiesReasoning, streaming, function calling, JSON mode and long-context
Pricing tierPaid-plan model; free plan covers plugsky-micro and plugsky-lite
APIOpenAI-compatible /v1/chat/completions — no SDK changes
ResilienceBackup upstream plus same-profile fallback peers
Product statusLive

TL;DR

  • Built for problems that require thinking before answering.
  • Best fits: math, logic, planning and multi-constraint decisions.
  • Use it as an escalation target, not an everyday default.
  • Ask for the conclusion explicitly — reasoning output can be verbose.
  • Validate with tests or rubrics, not by reading the chain of thought.

How it works, step by step

  1. Read the live model card at /models for window, limits and feature flags.
  2. Identify the questions that fail on your default model: math, logic, planning.
  3. Benchmark plugsky-reasoning on those hard cases against your current model.
  4. Verify answers with an objective test, calculation or rubric rather than prose.
  5. Keep routine traffic on faster tiers and escalate only hard cases.
  6. Review reasoning latency and quality after model-card changes.
1Read the live modelcard at /models forwindow, limits and2Identify thequestions that failon your default3Benchmarkplugsky-reasoningon those hard cases4Verify answers withan objective test,calculation or5Keep routinetraffic on fastertiers and escalate6Review reasoninglatency and qualityafter model-card

Try it yourself

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What plugsky-reasoning is

plugsky-reasoning is the reasoning-first profile in the Plugsky catalogue. It is intended for questions where a quick answer is not enough — arithmetic and logic problems, planning with several constraints, code analysis and decisions that require comparing options. It supports the standard OpenAI-compatible surface, including streaming, function calling and JSON mode, and is listed as 128K-class on the live model card.

Read /models for the current engine, limits and routing; reasoning behaviour can change when upstream models are updated.

When to choose it

Choose plugsky-reasoning as an escalation target: routine chat, classification and extraction stay on faster tiers, and genuinely hard questions come here. It is also a good evaluator — running your hardest cases through it tells you whether a cheaper model's failures are prompt problems or capability problems.

For synthesis across many documents or top-tier judgement, compare it with plugsky-frontier and plugsky-max; reasoning depth and general capability are related but not identical.

Reasoning trade-offs

Reasoning models spend more time before they answer, and their output can be verbose. Plan for both:

  • Ask for a short final answer plus the key steps, not a full transcript.
  • Set output limits so reasoning does not crowd out the conclusion.
  • Validate with a test or calculation — a fluent explanation can still be wrong.
  • Keep it off interactive paths where users expect instant replies.

Self-serve plans are flat monthly with fair-use usage, so check the live pricing page when sizing reasoning-heavy traffic.

How to switch to plugsky-reasoning

Switching is one model name on the same endpoint: {"model": "plugsky-reasoning", "messages": [{"role": "user", "content": "Solve step by step, then give the final answer on one line."}]}.

Compare it with your current model on a fixed set of hard questions, score the final answers objectively, and adopt it only where it visibly improves outcomes. Keep routine traffic on faster tiers.

Honest comparison

Dimensionplugsky-reasoningplugsky-frontier and maxFast general tiers
Best fitHard logic, math and planningHardest analysis and synthesisRoutine chat and extraction
Reasoning depthHighHighestModerate
Latency profileSlower than routine tiersSlowestFast
Context class128K-class128K-class128K-class
Use asEscalation for logic problemsEscalation for analysisDefault traffic
PlanPaidPaidFree or paid

Frequently asked questions

Is plugsky-reasoning free?

No — it is a paid-plan model. The free plan covers plugsky-micro and plugsky-lite with no card required, and a 14-day full-access trial lets you evaluate paid tiers first.

What is plugsky-reasoning best at?

Problems that require deliberation: arithmetic and logic, planning under constraints, code analysis and multi-criteria decisions where a fast answer is likely to be wrong.

Should I use it for everything?

No. It is slower than routine tiers. Keep ordinary chat, extraction and classification on faster models and route only genuinely hard questions to the reasoning profile.

How do I verify a reasoning answer?

Use an objective check wherever possible: run the code, recompute the number, or apply a rubric. A fluent explanation is not evidence that the answer is correct.

What context window does it have?

It is 128K-class today, but the live window and output limit are published per model on the catalogue.

Does it support tools and structured output?

Yes — streaming, function calling and JSON mode are part of the OpenAI-compatible surface, so it can act on its conclusions where supported.

How is pricing structured?

Self-serve plans are flat monthly with fair-use usage rather than per-token billing. See the live pricing page for current plans.