URL: https://postharvestreport.com/benchmark-report
Commercial cannabis post-harvest benchmarks for flower recovery, labor cost, bucking, trimming, grading and automation, based on field data and production testing across Canada and the United States.
The Post-Harvest Benchmark Report
By Jay Evans, Founder & CEO, Keirton Inc. Publisher: Post Harvest Report. Published: 2026. Last updated: .
The next decade of cannabis innovation will happen in post-harvest. A diagnostic framework for commercial post-harvest economics, and where AI is now changing what's possible.
Disclosure: the author is Founder & CEO of Keirton Inc., which manufactures post-harvest equipment including the Twister T-Zero Pro and the Marvel AI grading system.
Twenty-plus years in cannabis. Ownership in ten facilities. Toured 500+ grows across four continents. Equipment built at Keirton has processed over eighty million pounds of cannabis to date. From that vantage point, one pattern is hard to miss: the industry has spent a decade optimizing cultivation, and very little of that energy has reached post-harvest.
Genetics, lighting, nutrients, environmental control, plant care, that's where the money and talent have gone. Post-harvest has been treated as a labor problem to be managed rather than an engineering problem to be solved. It's the stage most operators measure least precisely, and the stage where yield, quality, and labor are actually won or lost.
$1.4M / yr, a five-point yield difference on five thousand pounds per month at greenhouse pricing. Most operators cannot tell you their post-harvest yield within five points. They can tell you plant counts, cycle times, HVAC tonnage, and nutrient costs to two decimals. The gap between cultivation rigor and post-harvest rigor is the single largest unforced error in cannabis economics today.
This report is a framework for closing that gap. It maps the architectures producers actually use, what each one costs, what each one yields, and where AI is now changing what's possible.
Commercial post-harvest is five stages: drying, bucking, trimming, sorting, and curing. This report focuses on the middle three. Within those, work can be done by hand, by machine, or in a hybrid arrangement. The five common configurations, with cost and yield ranges seen at scale:
Quality is not a third axis on this table; it is a constraint. Push cost down or yield up far enough and the flower is no longer worth what the price column assumes.
The framework anchors on greenhouse-grown flower at 2,000–10,000 lb/month. The architectures translate to indoor and outdoor; what changes is wholesale price and labor profile.
Labor reduction. AI vision systems grade flower faster and more consistently than humans. In one production deployment, AI sorting replaced a fifteen-person line for $750,000 in annual labor savings.
Yield improvement. AI between the trimmer and QC pulls flower out of the machine stream early when ready, and routes the rest for the right intervention. Across three independent production-scale evaluations on greenhouse and outdoor flower, this approach delivered yield gains of 3.6% to 8%. At greenhouse pricing on 5,000 lb/month, a 5-point yield gain is roughly $1.4M/year.
Intelligent stream separation. Defect screening removed ~3% of pre-pack flower as mold-affected, protecting product quality and reducing recall risk. Value-tier sorting recovered 37% of "smalls" as medium-or-larger and routed them to a higher-tier brand at a $150/lb price uplift.
Across five independent producer evaluations, AI-driven systems delivered documented annual value of approximately $1M to $6M per producer. AI vision typically adds roughly $1–$2 per pound to the operations cost basis at production scale.
Three forces are driving post-harvest into its decade: economic (dollars per pound at stake are large and growing), technical (AI vision is now commercially deployable in production), and competitive (margin advantages compound during consolidation). AI will move from single-stage tasks to managing whole automation lines as integrated systems, generating data that feeds back into cultivation, genetics, and operational planning.
Find where you sit. Identify the lever that matters for your operation. Execute. The producers who do this work in the next two to three years will define what best-in-class looks like for the rest of the decade.
Every figure is labeled by evidence type. Producer-reported figures have not been independently validated.
| Metric | Observed range | High-performing range | Evidence type | Notes |
|---|---|---|---|---|
| Full automation | ~$10/lb · 40–60% yield | n/a | Field Observation | Machine buck, trim and sort, minimal QC. |
| Lean hybrid | $20/lb · 45–65% yield | n/a | Field Observation | Hand buck, machine trim and sort, light QC. |
| Standard hybrid | $25–30/lb · 50–70% yield | ~70% yield ceiling | Field Observation | Cost and yield coupled through QC labor. |
| Fast full hand | $30–40/lb · 70%–low 80s yield | 70%–low 80s | Field Observation | Fast crew. |
| Slow full hand | $40–80/lb · 70%–low 80s yield | n/a | Field Observation | Lever is labor speed. |
| Metric | Observed range | High-performing range | Evidence type | Notes |
|---|---|---|---|---|
| Flower recovery | 45–70% (typical hybrid) | 75–82% A/B | Field Observation | Defoliated flower; denominator is dried biomass entering post-harvest. |
| Processing labor | $20–30/lb (typical hybrid) | $20/lb | Field Observation | Bucked, trimmed, sorted and graded flower. |
| Metric | Observed range | High-performing range | Evidence type | Notes |
|---|---|---|---|---|
| Yield improvement | +3.6% to 8% | n/a | Measured | Three production-scale evaluations. |
| Defect screening | ~3% of pre-pack flower removed | n/a | Measured | Mold-affected; one deployment. |
| Smalls re-graded | 37% recovered as medium-or-larger | n/a | Measured | One deployment. |
| Price uplift on re-graded smalls | $150/lb | n/a | Producer Reported | Producer's pricing. |
| Sorting labor replaced | $750,000 per year | n/a | Economic Model | Fifteen-person line; one deployment. |
| Documented annual value | ~$1M–6M per producer | n/a | Economic Model | Depends on scale and capabilities. |
| Added cost basis | ~$1–2/lb | n/a | Economic Model | Typical at production scale. |
The 2026 Post Harvest Report benchmarks are based on commercial cannabis production data and field observations collected primarily over the past 12 months across Canada and the United States.
Canada and the United States.
The most recent 12 months.
The producer-level field table comes from producer interviews; figures were quoted by producers, with scope and burden assumptions unverified unless otherwise noted. It is available on request, not published.
Cannabis production results vary by cultivar, flower structure, moisture condition, cultivation quality, facility practices, product specifications, market requirements and measurement methodology. These benchmarks should be used as reference ranges rather than universal performance guarantees.
Evans, Jay. “2026 Cannabis Post-Harvest Benchmark Report.” Post Harvest Report, 2026. https://postharvestreport.com/benchmark-report