Eight team workspaces compared: what team-grade means, what the single-vendor plans cost in 2026, and how to test the difference in two weeks
Jul 19, 2026 · 12 min read
A team where several people use more than one model, and where the context they build is worth sharing, needs a team workspace. A solo user is better served by a personal aggregator or a single seat, and a team that works entirely inside one vendor's ecosystem should keep the plan it already has. The eight workspaces compared on the same criteria below are Playgram, WorkLLM, nexos.ai, Langdock, TeamAI, Aymo, Magai and TypingMind.
Which one to buy is harder to see than it should be, because every product in the category promises every model. Personal aggregators, developer gateways and team platforms all offer some version of it, so the model list rarely decides the purchase on its own. The differences are in the setup around the models: whether memory is shared or stays with each person, whether the bill grows with every hire, and whether an admin can see what the team uses.
So this guide sorts those products into three kinds, to show which one you are shopping for. It covers what a product has to include before it counts as team-grade, what the single-vendor plans cost in 2026, and when a personal aggregator or a single plan is the better buy.
You have seen five products promise every model and want to know what separates them.
You want one bill and one access policy instead of a subscription per model.
You want shared context and model choice for the whole group, without rationing.
The individual setup worked, and now the rest of the team needs it too.
Four layers, each with a cost a team can feel by the end of the month: the bill, the daily workflow, the project context and the admin work.
Every tool charges separately for the same basic work: chat, drafting and summarising. As an example, four single-vendor team plans came to about $101 per person a month at July 2026 list prices. That total takes ChatGPT Business at $25, Claude Team at $25, Gemini Business at $21 and Grok Business at $301, 2, 3, 4. Your own mix may cost less, so read that total as an illustration rather than a rate. The shape of the problem is the same at any total: someone who opens a tool once a week still pays for a full seat, because there is no smaller unit to buy.
People move between three or four separate tools, copy prompts from one to the next, and upload the same brief again in each one. None of that time appears on an invoice, so nobody measures it. Knowledge workers already switch apps around 1,200 times a day, and it takes roughly 23 minutes to refocus after each interruption6. Two more tools add to that count every day.
Project context sits in personal accounts, so prompts, decisions and outputs stay with the person who wrote them. A teammate who picks the work up starts from an empty chat. Moving the same task to another model means writing the brief again, because one tool cannot read another tool's history. You attach the documents again and explain the house style again, and the second model does not know what the first one already ruled out.
No single view shows which model was used, why, or what each tool costs this month. That makes a simple question hard to answer, such as whether the team still needs all four plans. When a person changes tools or leaves, their prompts and history go with them. There is also no central place to give a new hire access or remove it on someone's last day, so you do it one vendor console at a time.
Five things make a workspace a team can work in, rather than a model menu with a login. A product missing one of them is built for a different buyer.
The workspace should include Claude, GPT, Gemini, DeepSeek, Grok and the rest, and it should add new models as they ship. Every product in the category claims this, so check the published list against the families your team uses today.
Model access is only half the job. List what your team does beyond chat: image and video generation, web research, document and spreadsheet work, code review, chats that leave nothing behind. A workspace that covers the models but not these leaves you buying a second product.
Workspace-level context is shared across the team and its projects. Every model can read it, and it stays in place when you switch models. Personal history belongs to one user, while shared context lets the whole team work from the same information.
An admin should see and cap what the team spends, set limits per person as well as across the group, and have one place to grant and remove access. Usage analytics by person and model turn that from a monthly surprise into something you can manage.
A light user should not cost the same as a daily power user. Workspaces differ here: some sell a pool of usage the group shares, others charge per seat, so check which shape you are buying. Price it against your own headcount, because below about five people one per-seat plan often costs less.
The multi-model workspaces a team is most likely to weigh up, judged on the same criteria and to one standard. Where a vendor does not document something, the cell says so.
This table compares multi-model team workspaces with each other. The single-vendor plans a workspace replaces are priced further down, under 'Priced per seat', and are not rows here. Pricing is the lowest-priced paid plan that covers five users, at the monthly rate, so a product whose entry plan holds fewer than five people is shown on the plan that holds them. Each cell cites the page that documents that cell rather than one pricing page per row. Plans, prices and memory behaviour change often, so confirm current details before relying on them. Figures checked August 2026 against each provider's own pages, and cells marked 'Manual test required' could not be confirmed from public documentation.
The same products again, on the criteria that decide day-to-day use: what the workspace does besides chat, what it connects to, what an admin can see and limit, and where your data goes.
These criteria decide daily use more than the model list does, and vendors document them very unevenly. 'Not publicly documented' means the official sources checked did not state it, and 'Manual test required' means the behaviour cannot be confirmed without trying it. Neither means the feature is absent, so read them as questions to put to the vendor. Checked August 2026.
The table below gives the published per-seat price of each major single-vendor team plan, billed monthly. These are the plans an all-in-one workspace is bought to replace.
Each of these is a good product inside its own model family. Most teams start shopping for a workspace after they have bought two or three of them. Prices change often and vary by annual vs monthly billing and by region. Figures checked July 2026, so confirm current pricing with each provider before purchase. Sources are listed at the foot of this page.
Ranked by how much each one changes the number. The first two are the structural multipliers on a per-seat stack, and the rest are the leaks an audit usually finds.
Team workspaces, personal aggregators and developer gateways all put many models in one place, and each one is built for a different buyer. The workspace comes first below because it is the subject of this guide.
A chat workspace gives the whole team every model, shared memory and admin controls. The pricing shape varies: some sell a pool of usage for the group, and others still charge per seat. For scale, four single-vendor team plans came to about $101 per person a month at July 2026 list prices1, 2, 3, 4.
Best for: Teams of about five people and up who use more than one model.
Strengths
Trade-offs
One subscription bundles many models for a single user, and most of these products charge by points or credits rather than by seat. Their plans run from a few dollars a month to a couple of hundred, and none of them sells a team plan.
Best for: Individuals, and anyone evaluating models on their own.
Strengths
Trade-offs
An API layer such as OpenRouter or LiteLLM sends your applications' traffic to many models through one endpoint. OpenRouter covers 300+ models and charges per token from prepaid credits, with no seats9.
Best for: Engineering teams wiring models into products.
Strengths
Trade-offs
This is one realistic flow for a product launch. The project context is set once, and every stage reads from it, so a teammate can pick up any step.
Every stage reads the same shared context, so switching model or teammate needs no re-briefing. A person reviews the draft before it ships and sends weak work back to the drafting stage.
Products in this category mean very different things by the word memory, and a demo makes all of them look alike. Four distinctions are worth drawing before you trust any product with real project knowledge.
A context window is how much text a model reads in one request, and it empties when the chat ends. Memory is context stored outside the chat and pulled back into later ones, on another day or another model. A larger window does not give a team the second thing.
Some keep chat history and nothing more. Some let you attach files and build a knowledge base by hand. Some learn automatically but keep what they learn private to one person. Some save it at a level the whole team can reach. Only the last of these stops a group explaining the same project again.
Once memory is shared it needs a boundary: what belongs to one person, what belongs to a project and its members, and what the whole organisation should see. Products draw these lines differently and some draw only one, so ask which boundaries exist rather than assuming yours are reflected.
Before you move knowledge in, check four controls. Someone should be able to see what was saved and why it was used, correct a wrong entry, limit who can reach it, and stop exploratory work from becoming permanent. Memory you cannot inspect or correct turns a bad assumption into a standing fact.
A vendor-neutral trial plan. It works for any product in the category and takes about two weeks end to end.
List the model families your team uses today and any you expect to want, then drop any candidate that is missing one. It is a quick filter, and it usually removes half the candidates before you start a trial.
Give three or four people two weeks on the trial, doing their real tasks beside the tools they already have. Prompts written for a demo make every product look good, so use the work those people already have that week.
Save the house style and a few standing decisions, then check a week later that a different person can see them on a different model. Personal memory and shared memory look identical in a demo, so this is the one thing worth testing on purpose.
Confirm that the vendor does not train on your data, check how long it keeps the data and where it runs, and find the setting that removes access when someone leaves. You are putting all your project context into one product, so read these terms more carefully than usual.
Cost the shortlist at your current headcount, at three more people, and at double. Per-seat and usage-based plans cross over at some team size, so a product that wins at your current size can lose at double. Teams usually forget to price the growth.
A multi-model team workspace is usually the right buy when several people use more than one model and the context they build is worth sharing. A solo user should buy a personal aggregator or a single seat. A team that works entirely inside one vendor's ecosystem should keep its one plan.
Four limits apply to all of this. Pricing and plan caps change fast, and two products called Business are rarely the same thing, so you cannot compare plans by name alone. Shared memory only helps when you can see its scopes and its controls, and a demo will not show you either. The only reliable test in the end is your own team's work over two weeks.
Several products now cover the same model families, so the model list rarely decides the choice. The differences are in the setup around them: where the context is stored, who can read it, and what the bill does after your next three hires. Test those three first, because a demo rarely answers them.
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Playgram will automatically choose the most cost-efficient model suitable for the task. It will be chosen by users in approximately 80% of requests. Your models for the remaining 20%:
If you bought each separately:
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