Agentic Index
Beam vs Prime Intellect (2026)
Both sell GPU backed infrastructure to agent teams for different halves of the lifecycle.
Beam is where agents run: open source serverless sandboxes with gVisor isolation, stateful snapshots and bring your own compute, free to develop with and 89 dollars a month for a team. Prime Intellect is where agents are trained and evaluated, pairing a GPU marketplace quoted across more than fifty providers with Lab, a reinforcement learning and evaluation platform spanning more than two thousand five hundred open environments. Teams doing serious reinforcement learning often end up with both.
Choose Beam if
- You are running agents in production and need isolated sandboxes with predictable per second billing.
- Stateful snapshots and bring your own compute fit how you deploy.
- Documented coverage is broader across integrations, security and triggers for production workloads.
Choose Prime Intellect if
- You are training or fine tuning agents, not just serving them, and reinforcement learning is the work.
- A marketplace quoting more than fifty GPU providers is how you want to buy compute.
- Access to a large library of open evaluation environments shortens your research loop.
| At a glance | Beam | Prime Intellect |
|---|---|---|
| Category | Agent infrastructure | Agent infrastructure |
| Entry price | Free Developer ($30/mo credits); Team $89/mo; open source self host; per second GPU and CPU | Usage based, priced per GPU hour with quotes from more than fifty providers; large clusters are quote based |
| Free / trial | Free Developer tier with $30 a month in credits, refreshed monthly | Open source stack and community environments are free to use; hosted compute and training are usage based |
| Pricing confidence | public exact | public partial |
| Feature | B Beam |
P Prime Intellect |
|---|---|---|
| Action & orchestration | ||
|
Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
Full / Explicit | Partial |
|
Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
Partial | Partial |
|
Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
Partial | No / Not documented |
| Knowledge & context | ||
|
Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
No / Not documented | No / Not documented |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
Partial | No / Not documented |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
No / Not documented | No / Not documented |
|
Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
Full / Explicit | Partial |
|
Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
Partial | Partial |
|
Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
Full / Explicit | Full / Explicit |
| Solution readiness | ||
|
Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
No / Not documented | Partial |
| Platform extensibility | ||
|
Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
Full / Explicit | Full / Explicit |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
Full / Explicit | Full / Explicit |
|
Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
Partial | Full / Explicit |
| Specialist automation | ||
|
Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
Partial | No / Not documented |
Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | B Beam |
P Prime Intellect |
|---|---|---|
|
Entry price Lowest public entry point |
Free Developer ($30/mo credits); Team $89/mo; open source self host; per second GPU and CPU | Usage based, priced per GPU hour with quotes from more than fifty providers; large clusters are quote based |
|
Pricing confidence How public the numbers are |
Public — exact | Public — partial |
|
Billing Primary billing axis |
per second and per millisecond compute (GPU, CPU, RAM) | usage based compute priced per GPU hour, plus inference API usage and hosted training and evaluation |
|
Variable cost Workload / overage exposure |
High variable cost | High variable cost |
|
Free tier / trial Try before you buy |
Free tier
|
No free tier
|
|
Buying motion Self-serve vs sales call |
Self-serve | Mixed |