Benchtop Sequencers Comparison: Multi-Omics Upgradability Options

Benchtop sequencing has moved beyond the question of how many reads an instrument can generate in a single run. For many biotechnology, pharmaceutical and translational research laboratories, the more important question is what the platform can become as research requirements change.

A laboratory may begin with targeted DNA sequencing and later add RNA-seq, whole-exome sequencing, single-cell experiments, spatial workflows or long-read analysis. Buying a sequencer therefore involves more than comparing throughput, read length and price. It also means evaluating whether the platform provides a credible path toward new applications without forcing the laboratory to replace its entire sequencing strategy.

That makes multi-omics upgradability an increasingly useful way to approach a benchtop sequencers comparison.

The term needs some qualification. A sequencer that accepts different library types is not necessarily a multi-omics instrument. A system with multiple flow-cell configurations may be highly scalable but still remain a conventional sequencing platform. Conversely, an integrated system may connect sequencing with cellular, protein or spatial measurements.

Current benchtop options span several technology models, including short-read systems such as the Illumina MiSeq i100 Series and NextSeq 1000/2000, Element AVITI platforms and PacBio Onso; compact long-read systems such as Oxford Nanopore PromethION 2 Solo and PacBio Vega; and newer integrated approaches such as Element AVITI24.

The goal of this comparison is not to identify one universal “best benchtop sequencer.” Instead, it examines which type of platform provides the most useful expansion path for different laboratory strategies.

What Does “Multi-Omics Upgradability” Actually Mean in a Benchtop Sequencer?

Before comparing platforms, it is important to separate several concepts that are often grouped together under “flexibility.”

Application flexibility versus true multi-omics capability

A conventional NGS platform may support DNA sequencing, RNA sequencing, targeted panels, exome sequencing, single-cell RNA sequencing or spatial transcriptomics through compatible library-preparation and analysis workflows.

That is valuable application flexibility, but it does not necessarily mean the instrument directly measures multiple biological modalities.

For example, a sequencing system can process libraries generated from a single-cell experiment while the actual cell partitioning, molecular tagging and sample preparation occur elsewhere. Similarly, a sequencer can process a spatial transcriptomics library without itself performing spatial imaging.

True multimodal workflows can go further by combining measurements such as transcriptomics, proteomics, epigenomics or morphology from the same biological system. Reviews of single-cell and spatial multi-omics emphasize that the scientific value comes not simply from generating multiple datasets, but from integrating information across molecular layers and, in spatial studies, retaining biological context.

This distinction is central to any benchtop sequencer comparison.

Four dimensions of upgradeability

A practical evaluation can divide platform flexibility into four dimensions:

1. Hardware:
Can the instrument itself be upgraded, expanded or exchanged for a higher-capacity configuration?

2. Chemistry and consumables:
Are different flow cells, read lengths, reagent configurations or chemistries available?

3. Workflow ecosystem:
Can the platform accommodate new library-preparation methods, single-cell assays, spatial workflows or other applications?

4. Informatics and integration:
Can the data feed existing analysis pipelines, cloud environments and multi-omics integration workflows?

A platform can be strong in one dimension and limited in another.

Why upgradeability matters for pharmaceutical and biotech laboratories

Research programs rarely remain static for the entire useful life of an instrument.

A molecular biology laboratory might initially need targeted sequencing for biomarker validation, then expand into RNA sequencing as a drug-discovery program develops. A translational team might add single-cell analysis to investigate cellular heterogeneity. A genomics group may eventually require long reads for structural variants or complex transcript isoforms.

The alternative to planning for this expansion is purchasing separate systems later, outsourcing new applications or replacing the original instrument.

However, buying excess capability also has a cost. A high-throughput system that is consistently underutilized can create unnecessary consumables, infrastructure, storage and operational expenses.

The Current Benchtop Sequencing Landscape

The term “benchtop sequencer” now covers systems with substantially different technologies and scales.

Short-read benchtop platforms

Short-read systems remain the most familiar option for routine DNA and RNA sequencing.

The MiSeq i100 Series occupies the lower-output end of Illumina’s current benchtop portfolio. Illumina lists output of approximately 1.5–30 Gb, 10–200 million paired-end reads and maximum read lengths of 2 × 500 bp, with stated run times of roughly four to 24 hours.

The NextSeq 1000 and 2000 sit substantially higher in throughput. With XLEAP-SBS chemistry, current specifications range from 10 Gb on a P1 flow cell for 2 × 50 bp sequencing to 540 Gb on a P4 flow cell for 2 × 150 bp sequencing. P3 and P4 configurations are available on the NextSeq 2000.

Element AVITI takes another approach, offering independently addressable flow cells and several output configurations. Current specifications include 15 Gb through 300 Gb configurations for conventional Cloudbreak workflows, depending on read length and flow-cell configuration.

PacBio Onso is a short-read platform based on sequencing-by-binding technology. Its current specification sheet describes 2 × 150 bp sequencing, approximately 800 million to 1 billion paired-end reads and 120–150 Gb of output per run.

These systems should not be treated as interchangeable simply because they all fit within the broad benchtop category.

Long-read benchtop sequencing

Long-read instruments answer a different set of biological questions.

The Oxford Nanopore PromethION 2 Solo is a compact system designed to run up to two independently addressable flow cells. It can operate with a GridION system or user computing infrastructure and supports real-time data streaming.

PacBio Vega, meanwhile, brings HiFi long-read sequencing into a benchtop system. PacBio currently specifies up to 90 Gb of HiFi data per run from a single SMRT Cell, with applications including genome sequencing, structural variant analysis, full-length transcriptome work and methylation detection.

These platforms are particularly relevant when the laboratory’s future needs include genome assembly, phasing, complex genomic regions, structural variants or full-length transcripts. Long-read sequencing can complement rather than replace short-read sequencing because the technologies address different analytical limitations.

Integrated multi-omics platforms

A newer category is emerging in which sequencing is only one part of the instrument’s capability.

Element positions AVITI24 as an integrated sequencing, screening and spatial-analysis platform. Its current specifications describe sequencing alongside RNA, protein and morphology profiling, with two independently addressable flow cells. Element lists up to 3 billion sequencing reads per dual-sided run and integrated profiling of up to 2 million cells per run.

That is fundamentally different from simply having a sequencer that can process libraries from multiple assays.

How the Major Benchtop Platforms Differ in Expansion Potential

The following comparison focuses on expansion potential rather than declaring a universal winner.

Specifications and upgrade offerings can change, so laboratories should verify current manufacturer documentation and commercial terms before procurement. The table is intended as a strategic framework rather than a substitute for instrument qualification.

Illumina’s Benchtop Path: From Routine Sequencing to Higher-Throughput Applications

Illumina’s main advantage in this comparison is not simply sequencing output. It is the breadth of the sequencing ecosystem around its instruments.

MiSeq i100 Series as a lower-scale entry point

The MiSeq i100 Series is relevant where a laboratory needs rapid, relatively small sequencing runs rather than maximum throughput.

Its current specifications include approximately 1.5–30 Gb output, maximum 2 × 500 bp reads and approximately four-to-24-hour run times.

That profile can suit targeted sequencing, microbial projects, small genomes and other studies where buying substantially more capacity would create unnecessary batching or wasted output.

Its limitation from a future-proofing perspective is not that it lacks applications. Rather, laboratories expecting to move toward much larger single-cell, exome or transcriptomic workloads may eventually need a higher-capacity platform.

NextSeq 1000 versus NextSeq 2000

The NextSeq family provides a clearer throughput expansion model.

The NextSeq 1000 supports P1 and P2 flow cells, while the NextSeq 2000 additionally supports P3 and P4. Current 2 × 150 bp specifications range from approximately 30 Gb on P1 to 540 Gb on P4.

That difference matters because throughput can be adjusted to project requirements rather than forcing every experiment onto the same scale.

Illumina also provides a formal trade-in pathway for eligible NextSeq 1000 instruments to move to NextSeq 2000. This is an example of an upgrade pathway, although it is different from adding a new modality to an existing instrument.

The application ecosystem is broad. Current manufacturer documentation covers exome sequencing, mRNA sequencing, single-cell RNA sequencing, targeted sequencing and spatial transcriptomics workflows.

Where Illumina fits in a multi-omics strategy

Illumina’s platforms can serve as sequencing engines inside broader multi-omics projects.

A single-cell workflow, for example, can combine transcriptomic sequencing with other molecular measurements. Spatial workflows can similarly produce sequencing libraries that retain tissue-level context.

For laboratories considering spatial multi-omics approaches, the important point is that the sequencer is only one component of the overall experimental architecture.

This makes Illumina particularly relevant for laboratories that want broad sequencing application flexibility, but that distinction should not be confused with native multi-omics measurement on the sequencing instrument itself.

Element AVITI and the Shift Toward Upgradeable Benchtop Platforms

Element’s AVITI family is especially interesting when the procurement question centers on explicit platform expansion.

AVITI’s flexible throughput model

Current AVITI specifications provide several sequencing configurations across different output levels and read lengths. AVITI can use dual flow cells with independent control, allowing laboratories to select different run scales according to project requirements.

This is useful when a core laboratory has highly variable workloads.

A small targeted experiment does not necessarily need the same sequencing capacity as a multi-sample exome or RNA-seq project. Flexible output can therefore function as a form of economic scalability.

AVITI LT → AVITI → AVITI24 as an upgrade pathway

This is one of the clearest examples of formal upgradeability in the current benchtop landscape.

Element states that AVITI LT can be upgraded to AVITI or AVITI24, while AVITI can be upgraded to AVITI24.

The significance is strategic.

A laboratory could start with a lower-throughput configuration, expand sequencing capacity as utilization grows, and potentially move toward AVITI24’s integrated multi-omics capabilities without adopting an entirely unrelated platform family.

However, “upgradeable” should never be interpreted as an unlimited guarantee of future capability. Procurement teams should establish:

• Which hardware components change
• Whether installation is performed onsite
• What capital expenditure is involved
• Whether the upgrade requires instrument downtime
• Which applications become available after upgrading
• What consumables remain compatible
• Whether the upgrade is contractually guaranteed or simply commercially offered

Element currently lists a specific AVITI24 upgrade option and describes the AVITI-to-AVITI24 path as part of its platform strategy.

AVITI24 and integrated multi-omics

AVITI24 changes the discussion because the platform extends beyond sequencing.

Element currently describes simultaneous profiling of RNA, protein and morphology, alongside NGS sequencing. Its specifications include two independent flow cells, approximately 24-hour runs for certain cytoprofiling workflows, and imaging at subcellular resolution.

The platform therefore represents a transition from:

sequencer → sequencing platform → integrated multi-omics platform

That distinction is more important than simply comparing gigabytes per run.

For research programs studying cellular phenotypes, drug response or disease microenvironments, the ability to connect molecular and morphological measurements can potentially change the experimental design itself.

At the same time, integrated capability does not eliminate the need for careful assay validation, sample preparation, computational analysis and complementary technologies.

Where Long-Read Benchtop Platforms Fit Into Multi-Omics Planning

Short-read and long-read sequencing should not be treated as two versions of the same instrument.

Oxford Nanopore PromethION 2 Solo

PromethION 2 Solo is designed around a different operational model. It can run up to two flow cells independently, allowing experiments to be started separately or concurrently. Data can be streamed in real time to GridION or user computing infrastructure.

That can be valuable for laboratories where sequencing decisions may evolve during a run or where rapid data generation matters.

Long reads are also useful for structural variation, repetitive genomic regions, haplotyping and full-length transcript analysis. Recent literature continues to highlight the role of long-read sequencing in resolving genomic structures that can be difficult to characterize using short reads.

PacBio Vega

PacBio Vega brings HiFi sequencing into a benchtop format.

The current system specification lists up to 90 Gb of HiFi data per run, with applications including microbial de novo assembly, targeted sequencing, full-length transcriptomics, human genome sequencing and methylation profiling.

This gives Vega a different form of expansion potential: not necessarily integrated multi-omics, but greater biological resolution through long, highly accurate reads.

For some laboratories, that is a more important form of future-proofing than adding another sequencing application.

Long-read versus short-read expansion

Long-read platforms can be particularly useful when future research involves:

• Structural variants
• Complex genomic regions
• Repetitive sequences
• Haplotype phasing
• Full-length transcript isoforms
• De novo genome assembly
• Certain epigenetic measurements

Short-read systems remain highly useful for:

• Large numbers of samples
• Targeted sequencing
• Exome sequencing
• Routine RNA-seq
• Many single-cell workflows
• High-throughput short-read applications

The result is that a laboratory planning broad genomics capability may ultimately benefit more from complementary platforms than from attempting to make one sequencer perform every possible task.

What Actually Makes a Benchtop Sequencer “Future-Proof”?

Future-proofing is not a specification. It is the combination of several forms of headroom.

Throughput headroom

Ask whether the platform can accommodate both today’s smaller experiments and tomorrow’s larger projects.

Important questions include:

• Are multiple flow-cell sizes available?
• Can independent runs be started separately?
• Can output be scaled without changing instruments?
• Will the laboratory need to batch samples unnecessarily?

NextSeq 1000/2000 and AVITI demonstrate two different approaches to this problem through multiple flow-cell/output configurations.

Application headroom

A platform becomes more strategically useful when its ecosystem can support several applications.

For example:

• DNA sequencing
• RNA sequencing
• Exome sequencing
• Targeted panels
• Single-cell sequencing
• Spatial transcriptomics
• Epigenomic workflows

Illumina’s current NextSeq application documentation illustrates how one sequencing platform can support many of these workflows through different library-preparation and analysis solutions.

Upgrade headroom

Not all “upgrades” are equal.

A software update may improve analysis without changing the physical instrument. A new chemistry may increase data quality. A larger flow cell can increase throughput. A trade-in can move the laboratory to a different instrument. A platform upgrade may add an entirely new biological modality.

These should be recorded separately during procurement.

Ecosystem headroom

The instrument is only one part of the workflow.

Laboratories should also evaluate:

• Library preparation
• Sample QC
• Bioinformatics
• Data storage
• Cloud computing
• Third-party kits
• Existing staff expertise
• Data-analysis pipelines
• Instrument service and support

A platform with impressive specifications can still be a poor long-term choice if it requires an ecosystem the laboratory cannot practically support.

Multi-Omics Upgradability Is Also a Workflow Question

Buying a multi-omics-capable instrument does not automatically create a multi-omics laboratory.

Sample preparation can become the limiting factor

Sample quality may determine the practical ceiling of an experiment.

Nucleic-acid extraction, RNA integrity, tissue handling, cell isolation, protein preservation, FFPE processing and library preparation can all influence downstream results.

A platform capable of multiple modalities is useful only when the laboratory can consistently generate compatible samples.

Data integration can be harder than data generation

Multi-omics produces heterogeneous datasets.

Transcriptomic, proteomic, morphological and spatial measurements can differ in scale, noise characteristics, resolution and data structure. Recent research continues to identify computational integration as a significant challenge in spatial and multimodal omics.

This means procurement teams should evaluate computational requirements alongside instrument specifications.

A laboratory may need additional:

• Storage
• GPU or CPU capacity
• Bioinformatics expertise
• Data-management systems
• Metadata standards
• Integration software

The laboratory may still need complementary instruments

Even an integrated platform does not eliminate the need for other technologies.

Depending on the research question, a multi-omics program may still involve:

• Mass spectrometry
• Imaging
• Flow cytometry
• Histology
• Proteomic assays
• Specialized sample preparation
• High-performance computing

The practical objective is therefore not to find one instrument that replaces the laboratory. It is to build an infrastructure strategy in which sequencing technology connects efficiently with the other measurement systems.

Comparing Platforms by Research Scenario Rather Than by Brand

The most useful way to interpret a benchtop NGS comparison is to start with the research pipeline.

Targeted and smaller sequencing projects

For laboratories primarily performing targeted sequencing, microbial work or smaller projects, systems such as the MiSeq i100 Series or AVITI LT may provide a more appropriate scale than a high-throughput platform.

The relevant question is whether the lower-output system provides enough application headroom for the laboratory’s expected workload.

Laboratories expecting sequencing-volume growth

For growing genomics facilities, NextSeq 1000/2000 and AVITI offer stronger throughput expansion options.

The NextSeq family provides multiple P-series flow cells, while AVITI provides several output configurations and independently addressable flow cells.

The better fit depends on expected sample volumes, existing workflows, informatics infrastructure and the laboratory’s preferred ecosystem.

Laboratories moving toward long-read genomics

PromethION 2 Solo and PacBio Vega should be considered when future research questions require long reads.

The choice between nanopore and HiFi approaches depends on factors such as read characteristics, real-time analysis requirements, desired accuracy, sample type, workflow and computational strategy.

Laboratories moving toward integrated multi-omics

AVITI24 represents a different procurement category because its value proposition extends into integrated RNA, protein and morphology profiling alongside sequencing.

For a laboratory already planning single-cell and spatial multi-omics, that distinction may be more important than conventional sequencing throughput.

Mixed short-read and long-read strategies

For many advanced genomics programs, a mixed-platform strategy can be rational.

Short reads can provide economical high-throughput sequencing for routine projects, while long reads can address structural variation, complex loci and full-length transcripts.

In this situation, “future-proofing” does not mean finding one instrument that does everything. It means ensuring that the laboratory’s infrastructure can connect the technologies without creating unnecessary workflow silos.

Procurement Questions to Ask Before Buying an Upgradeable Benchtop Sequencer

Questions about the upgrade path

Ask the manufacturer:

• What upgrades are officially supported?
• Is the upgrade hardware, software or both?
• Can the existing instrument be upgraded in place?
• Is a trade-in required?
• What capital expenditure is involved?
• How long does the upgrade take?
• What happens to existing consumables?
• Is future upgradeability included contractually?

A documented trade-in pathway, such as the current NextSeq 1000-to-2000 option, is different from an upgrade that changes the same instrument’s biological measurement capabilities.

Questions about consumables

Consumables can determine the practical economics of an expandable platform.

Ask:

• How many reagent configurations are available?
• Can low-volume studies be run economically?
• Are small and large flow cells available?
• What happens when sequencing volume increases?
• Are different applications compatible with existing consumables?
• How much library-preparation modification is required?

Questions about informatics

Procurement should also assess:

• On-instrument analysis
• Cloud compatibility
• Local computing requirements
• File formats
• Existing pipelines
• Secondary-analysis software
• Storage requirements

For example, NextSeq 1000/2000 systems currently support onboard DRAGEN secondary analysis as well as cloud and user-created pipelines.

Questions about multi-omics compatibility

For laboratories planning broader biological measurements, ask:

• Which modalities are directly supported?
• Which require separate instruments?
• Are the workflows commercially available?
• Which sample types are validated?
• What is the expected hands-on time?
• What downstream analysis is required?
• Are applications mature or still emerging?

These questions prevent a common procurement mistake: interpreting a vendor’s use of the term “multi-omics” as meaning that every omics workflow is natively performed on the instrument.

Buying for Today vs. Building for the Next Five Years

A sequencer can have a useful operational life while becoming strategically limiting much earlier.

When buying more capability than you currently need makes sense

Higher capability may be justified when:

• R&D programs are expanding rapidly
• Multiple sequencing applications are planned
• Single-cell or spatial research is already in development
• The instrument will serve multiple research teams
• A core facility expects increasing utilization
• The laboratory wants to reduce outsourcing

In these circumstances, throughput and upgrade headroom can have strategic value.

When a simpler platform is the better decision

A simpler system may be more rational when:

• The application range is narrow
• Sample volumes are consistently low
• Existing workflows are stable
• Specialized sequencing is outsourced
• Bioinformatics infrastructure is limited
• The laboratory has no near-term multi-omics program

The most technologically advanced system is not automatically the most efficient laboratory investment.

When a multi-platform strategy is more rational

A laboratory may deliberately divide its infrastructure:

Short-read sequencing: routine DNA/RNA, targeted sequencing and high-throughput projects.

Long-read sequencing: structural variants, complex genomes, phasing and full-length transcript analysis.

Proteomics: protein abundance, modification and functional measurements.

Imaging/spatial technologies: cellular localization and tissue architecture.

This approach can be more expensive in capital terms, but it can also prevent a single instrument from being stretched beyond the biological questions it is best equipped to answer.

Frequently Asked Questions

What should you look for when comparing benchtop sequencers?

Look beyond throughput and price. Compare read length, accuracy, output configurations, application range, consumables, library-preparation compatibility, informatics, service requirements and the manufacturer’s upgrade strategy. Most importantly, evaluate whether the platform can support the applications your laboratory expects to add over the next several years.

Can a benchtop sequencer support multi-omics research?

Yes, but the meaning of “support” varies. A conventional sequencer may generate data for single-cell, spatial or multi-omics experiments without directly measuring every modality. An integrated platform can combine sequencing with additional molecular or cellular measurements. These are different levels of multi-omics capability.

What is the difference between a scalable sequencer and an upgradeable sequencer?

A scalable sequencer can accommodate different workloads through flow cells, reagent configurations or throughput levels. An upgradeable sequencer has a more explicit pathway for changing the instrument’s capability, which may involve hardware, software, trade-in or additional application modules. Scaling and upgrading should therefore be assessed separately.

Are long-read benchtop sequencers suitable for multi-omics?

They can be important components of multi-omics strategies, particularly for transcriptomics, structural-variant analysis, genome assembly, phasing and some epigenetic applications. However, long-read sequencing itself does not automatically provide integrated proteomic, morphological or imaging measurements. Its value is often complementary to other omics technologies.

Is buying a multi-omics-capable sequencer always better than buying a conventional benchtop sequencer?

No. The appropriate choice depends on utilization, research objectives, workflow complexity, capital budget and available computational expertise. A laboratory that performs targeted sequencing may gain little from capabilities it rarely uses, while a research program already moving into integrated single-cell or spatial studies may place much greater value on those capabilities.

Conclusion

The most useful way to evaluate benchtop sequencers comparison is to treat multi-omics upgradability as a continuum:

Application flexibility → throughput scalability → workflow expansion → platform upgradeability → integrated multi-omics

A MiSeq i100-class system can make sense for smaller, rapid sequencing requirements. NextSeq 1000/2000 provides a broader short-read application ecosystem and substantial throughput scaling. AVITI introduces a particularly explicit upgrade pathway across the AVITI LT, AVITI and AVITI24 family. PromethION 2 Solo and PacBio Vega address a different expansion need by bringing long-read sequencing into compact laboratory formats. AVITI24 goes further by connecting sequencing with integrated cellular and multi-omics measurements.

The right procurement decision therefore depends less on identifying the instrument with the largest specification sheet and more on mapping the laboratory’s likely research trajectory.

For a laboratory expecting its sequencing requirements to remain narrow, a simpler platform may offer the best operational fit. For a growing genomics program, throughput and application headroom may matter more. For research teams already committed to single-cell, spatial or integrated multi-omics, the ability to connect multiple biological measurements may be the more important criterion.

Future-proofing is ultimately not about buying the most advanced sequencer available. It is about buying a platform strategy that can evolve with the science.