Top Tensorlake alternatives for AI agent sandboxes in 2026

Teams evaluating Tensorlake alternatives typically compare platforms on isolation model, session model, BYOC availability, GPU support, and whether the platform covers the full production infrastructure stack or sandboxes only.

The right platform depends on your workload requirements and where your team needs to deploy. The following dimensions determine whether a platform fits production agent infrastructure.

• Isolation model: Kata Containers, Firecracker, CloudHypervisor, and gVisor each offer different trade-offs between boot time and isolation strength. Shared-kernel containers provide weaker guarantees for untrusted code. See Kata Containers vs Firecracker vs gVisor for a technical breakdown.
• Session model: Ephemeral vs persistent, named sandbox support, suspend/resume capability, and whether session time limits apply. Some platforms cap sessions at 1 or 24 hours; others support indefinite runtime.
• Snapshot and state management: The ability to clone, branch, checkpoint, and restore sandbox state affects how teams manage RL rollouts, agent evaluations, and parallel workstreams.
• BYOC (Bring Your Own Cloud) support: For regulated industries or teams with data residency requirements, sandboxes must run inside the company's own cloud account. Most platforms in this space are managed-only or limit BYOC to enterprise contracts.
• GPU availability: Agents running inference, fine-tuning, or compute-intensive tasks need GPU access on the same platform as sandbox execution.
• Platform completeness: Production agent infrastructure typically also requires databases, background workers, APIs, CI/CD, and observability in the same control plane.
• SDK and language support: Python, TypeScript, CLI, SSH, and REST API access each affect how sandboxes integrate into existing agent frameworks.
• Compliance: SOC 2, HIPAA, GDPR, and data residency requirements vary by industry and geography.
• Pricing transparency: Billing models vary significantly. Some platforms charge for provisioned resources; others charge for active usage only. Cost at scale can differ by several multiples between providers.

The platforms below cover the main use cases: production agent deployments, SDK-first code execution, long-running coding environments, stateful agentic workflows, and ML inference pipelines.

Northflank provides microVM-backed sandbox infrastructure alongside a full production stack: databases, APIs, workers, CI/CD pipelines, GPU workloads, and observability, all running on Northflank's managed cloud or inside your own VPC.

Sandboxes on Northflank use Kata Containers, Firecracker, or gVisor depending on the workload's isolation requirements, with sandbox creation taking around 1–2 seconds end-to-end. Each isolation model offers different trade-offs between boot time and isolation strength, giving teams the flexibility to match the runtime to their threat model. For a technical comparison, see Kata Containers vs Firecracker vs gVisor and microVM vs gVisor.

A key differentiator is self-serve BYOC (Bring Your Own Cloud). Northflank supports deployment into AWS, GCP, Azure, Oracle, CoreWeave, Civo, bare-metal, and on-premises without requiring a sales call. This is particularly relevant for regulated industries and deployments where data residency is a hard requirement. See deploying sandboxes in your cloud for setup details.

Northflank supports on-demand GPU workloads running alongside sandboxes in the same platform. L4, A100 (40 GB and 80 GB), H100, H200, and other GPUs are available without quota requests. GPU pricing is all-in: the H100 rate of $2.74/hour covers GPU, CPU, and RAM as a combined rate. See GPU sandboxes and the GPU workloads documentation for full hardware details.

• Both ephemeral and persistent sandbox environments with no forced session time limits
• Multi-tenant microVM isolation via Kata Containers, Firecracker, and gVisor
• Self-serve BYOC across AWS, GCP, Azure, Oracle, CoreWeave, Civo, bare-metal, and on-premises
• On-demand GPUs (L4, A100 40 GB, A100 80 GB, H100, H200, and more) without quota requests
• Full workload runtime: APIs, workers, databases, CI/CD, and observability in one control plane
• API, CLI, and SSH access
• In production since 2021 across startups, public companies, and government deployments; SOC 2 Type 2 certified

Best for: Teams that need production-grade microVM isolation, no session time limits, self-serve BYOC, GPU workloads alongside sandboxes, or a complete infrastructure stack beyond sandboxes alone.

Pricing (PaaS): CPU at $0.01667/vCPU-hour, memory at $0.00833/GB-hour, billed per second. H100 at $2.74/hour all-in. Full details on the Northflank pricing page.

E2B provides sandbox infrastructure for AI agents with Python and TypeScript SDKs and Firecracker microVM isolation. Each sandbox runs in an isolated Linux VM with a dedicated kernel. The SDK supports integration with LangChain, OpenAI, and Anthropic tooling.

Sandboxes can run continuously for up to 24 hours on the Pro plan and up to 1 hour on Hobby. For longer workloads, E2B supports pause and resume: pausing resets the runtime window and preserves sandbox state. E2B does not provide GPU compute. BYOC is available on the Enterprise plan only, which requires contacting sales.

• Firecracker microVM isolation with a dedicated kernel per sandbox
• Python and TypeScript SDKs with AI framework integrations (LangChain, OpenAI, Anthropic)
• Default 2 vCPU / 512 MiB RAM; configurable up to 8 vCPU
• Session limit: 1 hour on Hobby, 24 hours on Pro
• No GPU support
• BYOC: Enterprise only, not self-serve

Best for: Teams building coding agents or code interpreter experiences that need Python and TypeScript SDK integrations and sessions within the plan time limits.

Pricing: Hobby plan is free with $100 usage credits. Pro plan is $150/month. Compute billed per second: 1 vCPU at $0.000014/s ($0.0504/hr), 2 vCPU at $0.000028/s ($0.1008/hr), up to 8 vCPU at $0.000112/s. Memory at $0.0000045/GiB/s ($0.0162/GiB/hr).

For comparisons, see E2B vs Modal, self-hostable alternatives to E2B, and Daytona vs E2B.

Modal is a Python-first serverless compute platform. Modal Sandboxes run on gVisor, which intercepts Linux system calls in user space rather than providing a dedicated VM kernel per workload. By default, sandboxes have no ability to accept incoming network connections and are not authorized to access other Modal workspace resources.

The default sandbox timeout is 5 minutes, configurable up to a maximum of 24 hours per session. For workloads that need to run beyond 24 hours, Modal recommends using filesystem snapshots to preserve state and restoring from a snapshot in a subsequent sandbox. Modal has no BYOC option; all workloads run on managed infrastructure.

Modal Sandboxes have separate pricing from standard Modal compute. The sandbox CPU rate is $0.00003942/core/second ($0.14191/physical core-hour, where 1 physical core equals 2 vCPUs). Memory for sandboxes is $0.00000672/GiB/second ($0.02419/GiB/hr). GPU workloads use standard Modal pricing. Regional and non-preemptible multipliers apply on top of base rates for production workloads (1.5–1.75× regional, 3× non-preemptible).

• gVisor isolation (user-space kernel interception; not a dedicated VM kernel per workload)
• GPU support across H100, A100 (40 GB and 80 GB), L40S, A10, L4, T4 at standard Modal GPU rates
• Python SDK; JavaScript and Go SDKs are available
• Default 5-minute session timeout, configurable up to 24 hours
• Filesystem snapshots for state preservation across sessions
• No BYOC; managed infrastructure only

Best for: Python-first ML teams running inference, training, or RL pipelines who need GPU access alongside sandboxing in one managed platform.

Pricing (Sandbox-specific rates): CPU at $0.14191/physical core-hour (2 vCPU equivalent), memory at $0.02419/GiB/hr, billed per second. GPU at standard Modal rates: H100 at $3.95/hr, A100 80 GB at $2.50/hr, A100 40 GB at $2.10/hr, L4 at $0.80/hr. Regional and non-preemptible multipliers apply.

For comparisons, see E2B vs Modal, Daytona vs Modal, and E2B vs Modal vs Fly.io Sprites.

Fly.io Sprites provides stateful sandbox environments for AI coding agents. Each Sprite is a persistent Linux environment running in a Firecracker VM. The filesystem is backed by tiered storage: an active NVMe layer for local working data and durable object storage underneath, so the same filesystem is available on every run regardless of whether the Sprite was inactive.

Sprites are named persistent environments. When a Sprite becomes inactive, compute is removed and billing stops. When a Sprite receives a new request, compute is reassigned and the Sprite comes up with the same data on the filesystem. Checkpoints take approximately 300 ms and preserve the full environment state, including installed packages, services, and policies. Sprites do not provide GPU support or BYOC; all environments run on Fly.io's managed infrastructure.

Each Sprite supports up to 8 CPUs and 16 GB RAM per run. Network access is isolated by default, with fine-grained layer-3 egress policies configurable per Sprite. Sprites are accessible via CLI, REST API, JavaScript, and Go clients.

• Firecracker VM isolation with a dedicated kernel per Sprite
• Persistent tiered storage: NVMe active layer backed by durable object storage
• Checkpoints in approximately 300 ms, preserving full environment state
• Up to 8 CPUs and 16 GB RAM per Sprite
• Fine-grained layer-3 network egress policies
• CLI, REST API, JavaScript, and Go clients
• No GPU support; no BYOC

Best for: Teams building coding agents or arbitrary code execution environments that need persistent, stateful VMs with idle-based billing and checkpoint/restore for long-running or intermittent sessions.

Pricing: CPU at $0.07/CPU-hour (measured by Linux cgroup CPU usage), memory at $0.04375/GB-hour (sampled from cgroup memory usage), hot NVMe storage at $0.000683/GB-hour, durable storage at $0.000027/GB-hour. $30 in trial credits included.

For comparisons, see top Fly.io Sprites alternatives and E2B vs Sprites.

Runloop provides microVM-isolated Devboxes for AI coding agents. Devboxes provide hardware-level isolation between tenants using a VM and container dual-layer security model. The platform includes integrated benchmark support: teams can run their agents against SWE-Bench Verified and SWE-smith on the Basic plan, with custom benchmarks available on Pro.

Suspend and resume are available on the Pro plan: compute billing stops on suspension, and storage billing continues. Snapshot and branch from Devbox disk state is also available on Pro. Blueprints allow pre-built, shareable Devbox templates with custom configuration. Repo Connections infer build environments from Git repositories. No GPU support is available on any plan.

• MicroVM-level hardware isolation between tenants (VM + container dual-layer)
• Both ephemeral and persistent Devboxes; suspend and resume on Pro and above
• Blueprints for pre-built, shareable Devbox templates
• Repo Connections for automatic build environment inference from Git
• No GPU support

Best for: Teams building AI coding agents that need stateful Devboxes with suspend/resume, and snapshot branching

Pricing: Compute billed per second. Devbox CPU at $0.108/CPU-hour, memory at $0.0252/GB-hour, Devbox storage at $0.00034236/GB-hour. Basic plan is free with usage charges. Pro plan is $250/month plus usage. Enterprise pricing is custom. All plans include $50 in trial credits.

For more, see Runloop alternatives.

Pricing as of May 2026. Verify current rates on each platform's pricing page before making cost decisions.

Modal rates shown are Sandbox-specific rates. Standard compute rates differ. Regional (1.5–1.75×) and non-preemptible (3×) multipliers apply to Modal for production workloads.

Not all sandbox platforms can run inside your own cloud account. BYOC support determines whether a team with data residency requirements or an existing cloud contract can use a platform at all. The table below shows which platforms support BYOC, what clouds they cover, and how access is granted.

Northflank is the only platform in this comparison with self-serve BYOC and publicly available pricing for that deployment model. For a detailed breakdown, see the AI sandbox pricing guide and top BYOC AI sandboxes.

The right choice depends on your team's starting point, infrastructure requirements, and the type of workloads your agents run.

Teams that need self-serve BYOC, GPU workloads alongside sandboxes, no session time limits, or a full infrastructure control plane beyond sandboxes alone will find Northflank the most complete option in this comparison. For related reading, see best enterprise AI sandbox platforms, best code execution sandbox for AI agents, and code execution environment for autonomous agents.

Tensorlake provides Firecracker and CloudHypervisor-backed microVM sandboxes for AI agent workloads. It supports both ephemeral sandboxes and named sandboxes with suspend and resume. Snapshots can be taken from running sandboxes and restored into new ones, with support for cloning and forking. A separate orchestration layer handles durable execution, fan-out, retries, queues, and timers for long-running agentic workflows. Python and TypeScript SDKs are available alongside a CLI and REST API. BYOC is available on the Enterprise plan via contact with sales. No GPU compute is offered.

Tensorlake does not offer GPU compute. Northflank and Modal both support GPU workloads alongside sandboxes. Northflank supports L4, A100 (40 GB and 80 GB), H100, H200, and other hardware with all-in pricing and self-serve access. Modal supports H100, A100, L40S, A10, L4, and T4 at standard Modal GPU rates with per-second billing. E2B, Fly.io Sprites, and Runloop do not provide GPU compute. See GPU sandboxes for a comparison.

Northflank is the only platform in this comparison with self-serve BYOC and publicly available pricing for that model. Deployment into AWS, GCP, Azure, Oracle, CoreWeave, Civo, bare-metal, and on-premises is available without a sales call. Tensorlake, E2B, and Runloop offer BYOC on enterprise plans that require contacting sales. Modal and Fly.io Sprites are managed-only. For more detail, see best BYOC sandbox platforms and top BYOC AI sandboxes.

Among the platforms in this comparison with transparent, publicly available pricing, Northflank has the lowest published CPU rate at $0.01667/vCPU-hour. For a full breakdown by workload type and deployment model, see the AI sandbox pricing guide.