Some links on this page are affiliate links: if you buy through them we may earn a commission, at no extra cost to you.
Neither Nodus nor Modal is the universal winner for GPU training. Nodus is the more attractive starting point when a long-running job is dominated by listed GPU cost and can use its available machines. Modal is often the better fit for short experiments, training tied to web endpoints or broader application workflows, and jobs that require a large RDMA-connected cluster—although multi-node access is currently restricted to private beta.
The practical choice depends on the complete run bill, not the GPU line item. Runtime, GPU count, CPU and memory, storage, region, plan fees, startup and teardown time, retries, capacity and checkpoint recovery can outweigh the advertised hourly rate. The figures below reflect vendor-published pages and a Nodus-authored comparison available in October 2026, not an independent benchmark.
As an Amazon Associate I earn from qualifying purchases.
How should you choose between Nodus and Modal for GPU training?
Start by matching the platform to the workload rather than choosing on brand or a single price. A small supervised fine-tune that runs for minutes may favor Modal’s per-second billing and integrated workflow tools. A many-hour job on a listed GPU may favor Nodus if its machine price and capacity produce a lower total bill. A multi-node run needs a separate access and networking check on either service.
| Choose Nodus first when… | Choose Modal first when… |
|---|---|
| Your run is long enough for GPU-rate differences to dominate. | You need preprocessing, fine-tuning and reinforcement-learning workflow components in one product. |
| The exact GPU, region and machine are available at the time you need them. | Your training is closely coupled to web endpoints or other application services. |
| You can validate the SDK surface and do not depend on features the compatibility layer does not support. | You need a documented path toward RDMA-connected clusters or a larger single-node configuration. |
| You are comfortable with beta status for multi-node training. | You prefer per-second compute billing and can account for separately billed CPU and memory. |
These are starting hypotheses, not guarantees. Run the same representative job on both services before committing production training.
#1 Best Overall
- Read Before You Buy — No Video Output: These adapters support charging and USB 2.0 data transfer, but cannot transmit video signals. Except for standard USB webcams (which use USB data only), they are not compatible with HDMI/DisplayPort cables, video-capable USB-C hubs, or docking stations with video output.
- Convert USB-A Ports to USB-C: Designed to connect USB-C earphones, cables, flash drives, card readers, and other USB-C accessories to standard USB-A ports. Plug-and-play with no drivers or software required.
- Aluminum Alloy Housing: Built with a sturdy aluminum alloy shell that aids in heat dissipation and protects against daily wear and scratches. Designed to maintain a stable and secure connection.
- Compact & Travel-Friendly: The ultra-compact design allows the adapter to stay plugged into your device without blocking adjacent ports or adding bulk, reducing wear and tear on your original USB ports.
- 12-Month Warranty: Backed by a 12-month manufacturer warranty for peace of mind. Designed to meet strict quality control standards for reliable everyday performance.
What do Nodus and Modal actually charge?
Nodus publishes whole-machine hourly prices, while Modal publishes GPU-task rates per second and bills CPU and memory separately. Comparing a GPU number alone can therefore produce a misleading result.
Nodus listed machine prices
Nodus’s official pricebook, version 2026.10.8 and effective October 1, 2026, lists provider-supplied machine usage at the provider’s cost divided by 0.875. Billing runs from machine creation until deletion is confirmed. The following are listed whole-machine GPU prices, not a guaranteed quote for every machine or region:
Free tools Windows power users keep installed
One-click scans. No signup required.
| GPU | Nodus listed price | Pricing qualification |
|---|---|---|
| H100 SXM | $3.29 per hour | Whole-machine list price, Nodus pricebook, 2026 |
| A100 80G | $1.99 per hour | Whole-machine list price, Nodus pricebook, 2026 |
| L4 | $0.89 per hour | Whole-machine list price, Nodus pricebook, 2026 |
| B200 | $6.49 per hour | Whole-machine list price, Nodus pricebook, 2026 |
Because the charge covers the machine, check how many GPUs, how much CPU and RAM, and what storage are attached to the selected machine. Prepaid credits, node charges and any interruption or retry time also belong in the estimate.
Modal’s published GPU-task rates
Modal’s pricing page lists GPU-task rates by second. Examples shown in October 2026 convert to these approximate GPU-hour equivalents:
| GPU | Modal rate per second | Approximate GPU-hour equivalent |
|---|---|---|
| H100 SXM5 | $0.001097 | $3.9492 per GPU-hour |
| A100 80 GB | $0.000694 | $2.4984 per GPU-hour |
| L4 | $0.000222 | $0.7992 per GPU-hour |
| B200 | $0.001736 | $6.2496 per GPU-hour |
The hourly figures are arithmetic conversions of the displayed per-second rates, not promises of a final job total. Modal says CPU and memory are billed separately, and the applicable plan, region and non-preemptible settings can change the bill. Its listed plans include Starter at $0 per month with $30 of included compute and Team at $250 per month with $100 of included compute; confirm current plan terms before budgeting.
What does a like-for-like estimate look like?
A useful estimate uses identical GPU count and elapsed runtime on both services, then adds non-GPU resources. For example, six hours on one A100 80 GB would be approximately $11.94 from Nodus’s $1.99 machine rate before considering any machine-specific details. Multiplying Modal’s displayed $0.000694-per-second rate by 21,600 seconds gives about $14.99 in GPU charges before Modal CPU and memory charges.
Nodus’s October 12, 2026 vendor-authored comparison reported a six-hour single-A100 LoRA fine-tune at $6.54 on Nodus versus $14.99 on Modal. It also reported 100 L4 GPU-hours at $43.00 versus $79.92, and 288 H100 GPU-hours at $748.80 versus $1,137.37. Those are calculations in Nodus’s comparison, not independently verified totals; the article notes that Modal CPU and memory charges were separate.
Rank #2
- 5-in-1 USB-C Hub: Experience comprehensive connectivity featuring a Power Delivery input, two USB-A 2.0 ports, a USB-A 3.0 port, and an HDMI port. (Note: The USB-C power delivery input port is only for connecting an external wall charger to power your laptop and cannot power peripheral devices.)
- 90W Pass-Through Charging: Achieve optimal charging with 90W pass-through power to your laptop, supported by a total input of 100W, with the hub reserving 10W for operational efficiency. (Note: Wall charger not included.)
- Quick Data Transfers: Accelerate your productivity with rapid data transfers using a high-speed 5Gbps USB 3.0 port and two 480Mbps USB 2.0 ports.
- 4K HDMI Display: Enhance your visual experience with a hub capable of delivering 4K resolution at 30Hz in both mirror and extend modes. Please note that this hub is compatible with MacBook (macOS 12 and newer), Windows 10 and 11, ChromeOS, and laptops equipped with DP Alt Mode and Power Delivery. Note: This device is not compatible with Linux.
- What You Get: Anker USB-C Hub (5-in-1, 4K HDMI), welcome guide, 18-month warranty, and our friendly customer service.
Use this formula for each candidate: (GPU rate × GPU count × active seconds or hours) + CPU + memory + storage + plan or credit effects + startup, teardown and retry time. Include idle time if a machine remains allocated while data is prepared or exported.
Which GPUs and machine sizes can each platform provide?
Hardware fit comes before price. A cheaper GPU that cannot hold the model, batch or optimizer state is not a cheaper run.
Modal’s documented selection
Modal’s GPU guide lists T4, L4, A10, L40S, A100 variants, RTX PRO 6000, H100, H200, B200 and B300 families. Several families support as many as eight GPUs on one machine. Requesting a larger configuration can take longer to schedule, so capacity and queue time must be tested for the region and date of your run.
The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Nodus’s availability view
Nodus’s GPU guide is organized around the machines currently exposed to you. It shows how to inspect available machines, GPU count, region class, hourly price and when availability was last checked. Since that inventory is time-sensitive, record the machine details immediately before launching and again when you plan a recurring job.
Checks to perform before selecting a shape
- Confirm GPU memory, not only the GPU model name.
- Check whether the machine has one GPU or multiple GPUs and whether your framework can use them efficiently.
- Verify region, current supply and expected wait time.
- Measure data-loading and checkpoint throughput on the selected machine.
- Price the full machine or task, including CPU and RAM differences.
How do multi-GPU, multi-node and RDMA options differ?
Both services expose multi-GPU paths, but multi-node access is not a routine, universally available feature on either platform.
Modal
Modal’s GPU guide states that multi-GPU training on a single node is supported, while multi-node training is in private beta and requires access through Modal support. Its training product describes multi-GPU nodes and RDMA-connected clusters. Ask for the exact node limit, network topology, framework configuration and price for your account rather than assuming the product description applies automatically.
Nodus
Nodus labels multi-node training as beta in its GPU guide. The guide does not establish a universal node count or a guaranteed interconnect for every machine. Confirm whether your account has access, what network performance is guaranteed, how nodes are placed, and how failed-node recovery is handled.
Rank #3
- Sleek 7-in-1 USB-C Hub: Features an HDMI port, two USB-A 3.0 ports, and a USB-C data port, each providing 5Gbps transfer speeds. It also includes a USB-C PD input port for charging up to 100W and dual SD and TF card slots, all in a compact design.
- Flawless 4K@60Hz Video with HDMI: Delivers exceptional clarity and smoothness with its 4K@60Hz HDMI port, making it ideal for high-definition presentations and entertainment. (Note: Only the HDMI port supports video projection; the USB-C port is for data transfer only.)
- Double Up on Efficiency: The two USB-A 3.0 ports and a USB-C port support a fast 5Gbps data rate, significantly boosting your transfer speeds and improving productivity.
- Fast and Reliable 85W Charging: Offers high-capacity, speedy charging for laptops up to 85W, so you spend less time tethered to an outlet and more time being productive.
- What You Get: Anker USB-C Hub (7-in-1), welcome guide, 18-month warranty, and our friendly customer service.
When multi-node should decide the platform
Make this a gating requirement only if your model cannot fit on one machine or your scaling target depends on high-speed interconnect. Obtain written confirmation of beta access and test a short distributed run with the same framework, rendezvous settings and checkpoint behavior you will use in production. A nominally available cluster that spends time waiting for nodes can cost more than a smaller, immediately available single-node job.
How do checkpointing, storage and recovery work?
Checkpoint behavior determines how much money a failed or preempted run costs. Test persistence and restore time, not just whether a product has a volume feature.
Modal’s approach
Modal’s training material recommends storing checkpoints in Volumes and describes reusable storage for training workflows. It also references customer-provided cloud buckets. Verify persistence across retries or preemption, write and read throughput, storage charges, and any egress when checkpoints leave the platform.
Nodus’s approach
Nodus’s comparison describes resumable state under /nodus/state. It says Nodus Volumes can import data from Hugging Face, git, URLs and S3. Confirm which state is automatically preserved, how a restarted machine discovers it, and whether imported or exported data incurs storage or transfer charges.
A recovery test worth running
- Start a short training job with checkpoints at a known interval.
- Stop or retry the job after a checkpoint is written.
- Measure time to allocate a replacement machine and resume.
- Compare the resumed loss step, optimizer state and output files with the uninterrupted run.
- Add the failed allocation, export and restart time to the cost model.
Which platform has the better training and application workflow?
Workflow integration can outweigh a lower GPU rate when training is part of a larger service.
Modal’s workflow emphasis
Modal presents workflows for preprocessing, supervised fine-tuning, reinforcement learning and cluster-based training. Its material also positions the platform alongside web endpoints and application deployment. That combination is useful when a training job shares code, data or operational controls with an online service, but you should still check Python versions, dependency packaging, secrets, networking and endpoint limits for your codebase.
Nodus compatibility and trade-offs
Nodus’s comparison describes a Modal-compatible API surface, while also identifying unsupported SDK features and behavioral differences. Compatibility therefore reduces porting effort but does not prove drop-in equivalence. Inventory the SDK calls your training launcher, data pipeline, logging, endpoint deployment and autoscaling code actually uses, then run them against Nodus before estimating migration savings.
Rank #4
- Dual Converters, Infinite Potential：Includes 2× USB C male to USB A female adapters and 2× USB A male to USB C female adapters. Perfect for a wide range of uses—tablets with Bluetooth keyboards, expand USB ports on macbook, and more. Two different converters for all your daily needs
- Next-Level 10Gbps & 3A Charging: No more slow 480Mbps, this usb to usb c adapter has a transfer speed of up to 10Gbps, allowing you to do more transferring in less time. This usb adapter fits both USB A and USB C charger, supporting up to 3A fast charging
- Upgraded Exquisite Craftsmanship: With an aluminum alloy housing and metal connector, the usbc to usb adapter is extremely durable and sturdy. Rigorously tested to withstand more than 10,000 times of plugging and unplugging, ensuring long-lasting performance
- Broad Compatible: The usb c to usb adapter widely supports all USB C/ USB A devices like laptops, tablets, cellphones, car chargers, and phone chargers. Such as compatible with MacBook Pro/Air 2023/2022, Thunderbolt 4/3 Devices,Apple MagSafe Watch 9/8/7/SE/Ultra, iPad Pro 2022/2021, Samsung Galaxy S23/S20/S10, and iPhone 17/16/15 Pro. Plug and play
- Please Note: To reach 10Gbps speed, keep the cable under 3.3 ft. For USB A Male to USB C adapters, try flipping the USB C connector. USB C Male to USB A adapters support bidirectional 10Gbps transfer within 3.3 ft
Operational questions to ask
- Can the same container and Python environment run without code changes?
- Where do credentials, datasets, logs and checkpoints live?
- Do you need a web endpoint, scheduled job, interactive shell or only batch training?
- How are failures surfaced and how can an operator resume a run?
- Can you export weights and metadata without changing your downstream tooling?
What do the published pilot results prove—and what do they not prove?
Nodus reported two small pilots conducted October 11, 2026. Both used Qwen2.5-0.5B on one NVIDIA L4, one seed and one accepted run per platform. Nodus said the resulting weights were byte-identical and reported these recorded-charge differences:
Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minutePC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11| Pilot | Nodus-reported result | Important limitation |
|---|---|---|
| Supervised fine-tuning | 67% lower recorded charges | One GPU, one seed and one accepted run per platform |
| Continued pretraining | 42.5% lower recorded charges | Same narrow setup; not a broad workload benchmark |
| Fine-tuning including a failed Nodus attempt | Reported saving fell to 24.7% | Shows how retries can materially change the outcome |
| Export time | 11.0 minutes on Nodus versus 7.7 minutes on Modal | Single pilot measurement, not a general transfer-speed claim |
These results are vendor-reported evidence for one small model and configuration. They do not predict performance, reliability or savings for larger models, different datasets, other GPU shapes, distributed jobs or a different region. Reproduce the measurement with your own representative workload.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can you run a fair Nodus-versus-Modal pilot?
A controlled pilot turns published rates into a decision based on your actual code and failure profile.
- Freeze the workload. Use the same model revision, dataset snapshot, batch size, sequence length, precision, optimizer, number of steps and random seed.
- Match hardware. Select the closest GPU memory, GPU count and region on each service. Record the exact machine shape and availability timestamp.
- Measure end-to-end time. Record queue, boot, dependency installation, data staging, active training, checkpointing, export and teardown separately.
- Capture every charge. Export GPU, CPU, memory, storage, plan, credit, transfer and retry charges rather than relying on a single dashboard total.
- Test interruption recovery. Force or wait for a restart after a checkpoint, then measure resumed progress and additional allocation time.
- Repeat enough to expose variance. One successful run can hide capacity delays or transient failures; repeat across the conditions that matter to your schedule.
- Evaluate outputs. Compare final weights, validation metrics, logs, exported artifacts and reproducibility—not only elapsed time.
What are the most common decision mistakes?
Choosing the lowest advertised GPU rate
Modal’s per-second GPU figure excludes separately billed CPU and memory, while Nodus’s listed figure is for a whole machine. Build a full-job estimate before declaring a winner.
Assuming beta distributed training is production-ready
Modal’s multi-node path is private beta and Nodus labels multi-node training beta. Confirm access and test failure handling before making either service the foundation of a large cluster run.
Recommended Free Tools
Ignoring allocation and export time
Per-second billing does not make queue, boot, staging or export time free. A job that trains quickly but spends a long time waiting for capacity can miss a deadline or lose its cost advantage.
Porting only the training script
Dataset mounts, checkpoint paths, secrets, logging, endpoint deployment and cleanup often contain the platform-specific work. Test the complete launcher and recovery path, not just the forward and backward pass.
Best Value
- 5-in-1 Connectivity: Equipped with a 4K HDMI port, a 5 Gbps USB-C data port, two 5 Gbps USB-A ports, and a USB C 100W PD-IN port. Note: The USB C 100W PD-IN port supports only charging and does not support data transfer devices such as headphones or speakers.
- Powerful Pass-Through Charging: Supports up to 85W pass-through charging so you can power up your laptop while you use the hub. Note: Pass-through charging requires a charger (not included). Note: To achieve full power for iPad, we recommend using a 45W wall charger.
- Transfer Files in Seconds: Move files to and from your laptop at speeds of up to 5 Gbps via the USB-C and USB-A data ports. Note: The USB C 5Gbps Data port does not support video output.
- HD Display: Connect to the HDMI port to stream or mirror content to an external monitor in resolutions of up to 4K@30Hz. Note: The USB-C ports do not support video output.
- What You Get: Anker 332 USB-C Hub (5-in-1), welcome guide, our worry-free 18-month warranty, and friendly customer service.
Treating a vendor pilot as a benchmark
The reported L4 pilots are useful as examples of how costs can differ, but their one-model, one-seed design cannot establish a general speed or savings winner.
What is the practical decision rule?
Use Nodus when your measured all-in cost is lower on the required machine, capacity is dependable, and your code works with its SDK and storage behavior. Use Modal when its integrated training and endpoint workflow saves engineering time, its per-second model suits short or bursty jobs, or you obtain the multi-GPU or RDMA access your workload requires.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
If both pass the technical checks, choose based on the repeated pilot’s total cost per completed run, including failed attempts and operator time. Recheck prices, GPU supply and beta status immediately before a production commitment because all three can change.
Frequently Asked Questions
Can I use academic or startup credits with either service?
Modal documents academic and startup credit programs, and it also describes purchasing through AWS and Google Cloud marketplaces. Eligibility, application requirements and the amount of credit are subject to current program terms, so confirm them directly before putting credits into a forecast.
How many GPUs can Modal place on one machine?
Modal’s GPU guide says several GPU families support up to eight GPUs on a single machine. The exact families, available capacity and scheduling time vary, so request the specific shape rather than assuming every listed GPU can be configured eight-wide.
What should I record for an internal cost comparison?
Save the machine or task identifier, GPU count, region, start and stop timestamps, CPU and memory allocation, storage activity, transfer volume, retries and final artifact size. Keeping those records lets you reconcile the platform bill with the elapsed-time measurements after the pilot ends.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Is a byte-identical model output proof that the platforms perform the same?
No. Identical weights in one controlled run show that the selected configuration reproduced the output, but they do not establish equal throughput, availability, failure rates, scaling behavior or results on another model and dataset.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
