Sampling techniques

·    The Mineral Resource estimate for the Sierra Gorda copper deposit was completed using a total of 1,920 diamond drill holes (DD) and reverse circulation (RC) drill holes, corresponding to 579,614m.

·    A heterogeneity study, to determine the appropriate sample size was updated by Sierra Gorda SCM in 2023. The sample reduction and preparation is in line with the study.

·    A quarter of the RC sample volume and half cores were processed and analysed for every forty sample (duplicate) to assess sample representivity. Analytical results for duplicate samples were within 90% of accepted pairs with less than 30% relative error. Certified Reference Materials (CRMs), blanks, and duplicate samples are routinely included as part of the QA/QC program. Laboratory equipment is regularly calibrated and monitored through internal quality control procedures to ensure the accuracy, precision, and reproducibility of analytical results.

·    Samples from DD and RC drilling were collected at 2m intervals. For RC drilling, the samples collected from 2m intervals (up to 80kg) were reduced by riffle splitter to 10kg and sent to the laboratory. At the laboratory, 10kg samples were crushed to 90% passing 1.65mm. The crushed samples were reduced to 1,000g using a lineal cutter (CRC, Crushing Robotic Cell) and the 1,000g samples were pulverised to 95% passing 0.104mm. For DD, prior to 2021, half cores were used for sub-sampling for chemical analysis. Since 2021 to 2023, only quarter cores have been used; the other quarter is used for geometallurgical assessment. Half and quarter DD core samples from 2m intervals (approx. 3kg to 4kg) were crushed to 90% passing 1.65mm. The crushed samples were reduced to 1,000g using a rotary splitter and then pulverised to 95% passing 0.104mm. Since 2024 to date, half cores were used for sub-sampling for chemical analysis. Finally, 1g pulp samples were subjected to chemical analysis using acid digestion (nitric acid at 95% concentration and hydrochloric acid) followed by Atomic Absorption Spectroscopy (AAS). A 30g to 50g charge was used to determine gold (Au) grade using the fire assay method, followed by AAS.

Logging

·    All DD cores were logged for lithology, alteration, mineralisation, veins and structures, as well as geotechnical data, including rock quality designation (RQD), fracture frequency (FF), fault type, and fill.

·    Representative RC chips were collected from each RC drill interval in a sample tray and were logged for lithology, alteration, and mineralisation. The geological parameters required for developing a geology and mineralisation model are pre-defined in the logging software. For consistency, the pre-defined codes are used for logging when entering information in the centralised database.

·    After logging, all drill holes undergo a geological validation process, comparing the geology with current models. The boundaries of the different mineral zones defined during drill hole mapping are adjusted once the chemical analyses are received. Following this validation, they are officially entered into the resource database.

·    Geological logging is both qualitative and quantitative in nature. The quantitative assessment reflected the prediction of the occurrence and abundance of mineralisation. The DD cores were photographed in their entirety. The geological description has the appropriate level of detail to properly support the development of a geology and mineralisation model. The entirety of the drill holes have geological mapping recorded in the database.

Sub-sampling techniques and sample preparation

·    All DD cores for every 2m interval were longitudinally cut into equal halves. One half to be used for chemical analysis and the other half was stored in the core library. If necessary, a quarter of the core will be cut for geometallurgical testing. The approximate weight of a 2m half core sample is between 6kg and 8kg. The whole half core samples were sent to an external laboratory for processing and chemical analysis. Until 2021, DD cores were cut into two equal parts at intervals of 2m, with one half used for chemical analysis and the other stored in the core library. A 2m RC interval weighs approximately 80kg. Samples are reduced to 10kg using a riffle splitter and sent to an external laboratory for processing. Since 2021 to 2023, only quarter cores have been used; the other quarter is used for geometallurgical assessment. Then, from 2024 to the present, the practice of cutting the core into two equal parts was resumed.

·    RC samples are weighted to confirm the weight received and then dried in an oven at 105°C (+5°C) for approximately 6 to 10 hours. For RC drilling, a 2m sample (up to 80kg) is reduced to 10kg with a riffle splitter and sent to the laboratory. At the laboratory, the 10kg samples are crushed to 90% passing 1.65mm and reduced to 1,000g using a lineal cutter (crushing robotic cell (CRC)). The 1,000g samples are pulverised to 95% passing 0.104mm.

·    Core samples: For DD, half core samples from 2m intervals (approx. 6kg to 8kg) are crushed to 90% passing 1.65mm. The samples are then dried in an oven at 105°C (+5°C) for approximately 6 to 10 hours. The crushed samples are reduced to 1,000g using a rotary splitter and then pulverised to 95% passing 0.104mm. The pulverised samples are passed through a rotary divider to obtain three pulps of 200g each. One of the portions is used for chemical analysis by AAS and the remaining two are stored as duplicates for future reference.

·    All sample collection processes from the drill holes (Diamantine and Reverse Air) and their corresponding mechanical preparation have been based on the various heterogeneity tests performed at the Sierra Gorda Mine in 2023 and the periods leading up to these, in accordance with industry standards. Thus, the mechanical preparation of the drill hole samples complies with the Sampling Nomograms, which are previously delivered to the external laboratories with which we work.

Quality of assay data and laboratory tests

·    A 1g pulp sample is digested using nitric acid and hydrochloric acid and thereafter quantified using AAS. This is considered appropriate for the type of mineralisation. The method is used to determine TCu and Mo percentages. A 30g to 50g charge is used to determine gold (Au) grade using the fire assay method followed by AAS. Samples are analysed in batches of 25. A batch contains 20 samples, two certified reference material (CRM), one pulp duplicate, one field duplicate and one blank sample. The analytical laboratory manages an internal quality control protocol that is performed on each batch analysed. The protocol includes analysis of three each of CRMs, duplicate samples and blank samples per batch. The results from the laboratory's internal control samples are reported on each certificate of analysis delivered.

·    Quality control of chemical analyses (Total Copper and Total Molybdenum) in drilling campaigns has been implemented as a process since 2014 and formalised since 2019 with 20% controls per batch. This includes field and pulp duplicates, insertion of standards, reference materials prepared from mine materials and internationally certified reference materials (Oreas), coarse blanks and pulp blanks. All of these controls correspond to blind inserts. Analysis of the results is performed in internal Drilling Management Software, with acceptance levels of 30% for field duplicates and 10% for pulps; 5 times the detection limit for blanks and three standard deviations for "standards" or two consecutive values above or below two standard deviations.

·    Currently, duplicate pulp samples are not sent to another independent laboratory (check or umpire analysis) to assess whether there is procedural bias at GeoAssay, the primary laboratory. The Competent Persons consider that the nature and quality of the chemical analyses and laboratory procedures are appropriate to support estimation of the mineralisation grades of the Sierra Gorda deposit.

Verification of sampling and assaying

·    All logging and chemical analysis is peer reviewed to confirm the geology (using core photographs) and mineralisation match with the analytical outcome. Once verification is complete, the data is authorised for inclusion in the central database.

·    Drill holes have not been twinned due to the disseminated nature of mineralisation and the low 'nugget' effect. The assessment is confirmed on review of semi-variogram models and provides confidence in the predictability of drilling results over short and long ranges.

·    The logging is performed on digital tablets, which are loaded as CSV files directly to the database. The results of chemical analyses are digitally recorded (in CSV files) and uploaded to a database in the SQL server.

·    Sierra Gorda SCM (SGSCM) has procedures in place for periodic back up of all information, including storing periodic backup offsite.

·    No adjustment has been made to the analytical data. For estimation purposes, values reported as less than the detection limit by the laboratory were assigned a value of half of the detection limit.

Location of data points

·    The mining concessions allow mining exploitation and exploration in Chile and are regulated by the Mining Code, which establishes the UTM coordinate system in Datum PSAD56 to be used as the official coordinate system. The local coordinate system developed by the mine is linked to the official coordinate system. The location of drill hole collars is surveyed by the survey department, using Trimble R12i equipment (global navigation satellite system), with a real-time kinematic accuracy of 8mm (horizontal) and 15mm (vertical).

·    Geodetic satellite positioning equipment (GPS) (TOPCON brand - GR3 model, double frequency, with accuracy of 5 mm) is used for geographical location and planimetry. A Total Topcon Station model 7501 is used to determine surface distances and an electronic LEICA level, model DNA3, is used to define precision elevations in the mining area.

·    Downhole surveys are performed with a gyroscope (model STO Gyro Master). The measurement is taken at downhole intervals between 20m and 50m from the end of the hole. The company conducting the downhole survey (Datawell) provides the data for each hole, which is then lodged in the database. SGSCM is in the process of preparing a procedure to validate all survey and depth information.

·    Surveying procedures and practices are adequate and can be used for mine planning purposes.

Data spacing and distribution

·    No exploration results are reported.

·    Due to the variable orientations of the drill holes, data spacing may vary with depth. In general, drill hole collars are spaced between 50m and 100m. Infill drilling is spaced between 30m and 60m (Figure 3).

·    The scheduling of twin drilling will be considered by the project team during future campaigns.

·    Drill spacing is considered sufficient by the Competent Persons to establish geological and grade continuity necessary to support a reliable resource estimate.

·    All samples are composited to 8m along the drill hole. The composite length is appropriate for panel grade estimation with a block height of 16m.

Orientation of data in relation to geological structure

·    Most of the drill holes are orientated in the east-west direction, with variable dip. However, there are also a small number of east-northeast orientated drill holes, and some of the shallower drill holes in the active open pit area have a radial pattern.

·    The general orientation of mineralisation within the hypogene zone is sub-vertical, with a north-northeast orientation in plan view. The drill holes are planned with an orientation that allows lateral recognition of the main body, to enable edge variability to be controlled. Within the mineralised body drilling confirms the mineralised zones and provides reasonable confidence in defining the mineralisation.

·    Even though the mineralisation is structurally controlled, the structures radiate in all directions, which means that drill cores are not generally oriented.

Sample security

·    Each sample generated is assigned a number by an automated numbering system which allows traceability at all stages of the process.

·    The samples are sent to the GeoAssay laboratory in Antofagasta for preparation and chemical analysis according to a defined procedure as described above. Transport is adequate to maintain the integrity and safety of the samples. The results are received and are verified for storage in a custom SQL server database.

·    The SQL database has user-level security and there are periodic backups of the server according to SGSCM procedure.

·    Pulverised samples (sieve mesh #150) are stored in envelopes (250 g), while coarse rejects (sieve mesh #10) are kept in plastic containers (1.0-2.0 kg). All material is properly inventoried and stored in larger containers to ensure sample integrity. Diamond drill cores are stored in wooden trays, whereas reverse circulation (RC) samples are kept in wooden and/or plastic boxes.

Exploration done by other parties

·    The historical drilling of the Sierra Gorda deposit began in 1966 with the first surveys by ITT, Cimma Mines and Chevron. The companies drilled 108 drill holes (95RC-13DD) before 1987. Between 1991 and 1996, Outokumpu began the first formal exploration campaign, completing 238 drill holes (109RC-48DD-81 mixed). Between 1997 and 2003, RTZ drilled 61 holes (53RC-8DD). Two companies, Teck-Cominco and SOQUIMICH, drilled 61 holes (44RC-8DD-17 mixed) between 1997 and 2011 on the Pampa Lina property. In parallel, Quadra drilled 1,069 holes between 2004 and 2012.

Geology

·    The Sierra Gorda deposit is located in the plain of the Intermediate Depression or the Intermediate Valleys located between the Cordillera de la Costa and the headwaters of the Cordillera de Los Andes.

·    Exploration and research associated with Andean metallogenesis identified three metallogenic belts from different ages related to hydrothermal systems, with copper, molybdenum and gold mineralisation, between 20° and 27° south latitude. Metallogenic belts are differentiated by an area to the west located in the coastal zone of Cretaceous age (130Ma), a central zone of Paleocene-Early Eocene age (66Ma to 55Ma) and an eastern belt of Upper Oligocene age (42Ma to 31Ma). All the world-class copper porphyry deposits that exist in northern Chile are located at the source of the Cordillera de Domeyko and its continuation to the north.

·    Sierra Gorda is located in the Palaeocene-Early Eocene metallogenic belt, located at the western edge of the Domeyko range in the second region of northern Chile.

·    Regionally, a sequence of Early Cretaceous volcanic rocks that was intruded by a granitic complex of Palaeocene age and a series of smaller, younger intrusions, have served as host rocks for numerous hydrothermal mineralisation systems of copper, molybdenum and gold (Figure 2).

·    The main structural systems are defined by regional faults of north-south and northwest direction, which control and serve as conduits for fluid alteration of the host rock and for deposition of economic mineralisation.

·    Figures 5, 6 and 7 show South West to North East cross sections of the lithology, alteration and mineralisation models, respectively.

Drill hole information

·    Exploration results are not reported as part of the Mineral Resource estimate.

·    Figure 3 shows the collar location of the drilling information used to develop the Mineral Resource estimate.

·    A metal equivalent has been used for reporting the Mineral Resource estimate.

Relationship between mineralisation widths and intercept lengths

·    The main ore body is vertical, and the dominant drilling orientation is east-west, with variable dips (vertical to 65°) depending on the location of the drill hole collar. Where mineralisation is disseminated or stockwork in nature, drilling also uses a variety of dip angles (vertical to 65°).

Diagrams

·    Relevant maps and sections are appended to this document.

Balanced reporting

·    Exploration results are not specifically reported as part of the Mineral Resource estimate.

Other substantive exploration data

·    SGSCM is currently conducting a geological survey (lithology, alteration and structural system) of the entire mining property and geophysics studies (IP-MIMDAS and magnetometry).

Further work

·    SGSCM is completing annual infill drilling programs to further enhance confidence in the Mineral Resource estimate within the Catabela Pit and to identify potential extensions to the deposit. In parallel, exploration is ongoing outside the existing pit shell to assess the continuity of mineralisation laterally, with emphasis on known structural trends and other potential satellite deposits.

Database integrity

·    The analytical results, once received, are verified and stored in a custom SQL server database. Since the start of mining in 2014, data on collars, downhole surveys, geological logging and analytical results have been loaded from CSV files as it becomes available. The upload process includes validation checks for consistency, including assessment of anomalous values.

·    As part of updating the geological model, all records are reviewed by experienced geologists against core photos in the context of the surrounding geological interpretation.

·    Measures are taken to ensure that data has not been modified, for example, due to transcription or typing errors, between initial collection and use for Mineral Resource estimation purposes. The process of validation is repeated annually.

Site visits

·    Ms. Leyla Vaccia is an employee of Sierra Gorda SCM and is based at site and has ongoing direct involvement with the operation. Regular observations and inspections of mining, sampling, geological logging, and resource estimation activities are conducted as part of her normal duties.

Geological interpretation

·    The geological model has been developed using lithology, mineralisation and alteration. Leapfrog software is used in developing 3-D volumes for geology and mineralisation.

·    The interpretation criteria considered for the lithological units is based on the conceptual model of the deposit, which considers a volcanic sequence (Quebrada Mala Formation, Maastrichtian; 73Ma to 65Ma), which is in contact with the Sierra Gorda intrusive complex (71Ma to 65Ma). Both units host porphyry bodies (Figure 2).

·    The alteration considers the interpretation of four main units (biotite, propylitic, sericite quartz and argillic), with biotite alteration being dominant. Biotite alteration is mainly characterised by pervasive replacement of mafic minerals by secondary biotite. The propylitic alteration is located in the periphery of the deposit. The sericite quartz alteration corresponds to the main hydrothermal alteration, presenting a wide spatial distribution affecting intrusives, volcanic rocks and intra-mineral porphyries. The argillic alteration is identified in the most supergene zone of the deposit and has a close genetic relationship with the secondary processes of sulphide leaching.

·    Copper mineralisation is defined on the basis of consideration of the following criteria.

o  A hypogene zone is defined, which corresponds to the mineralisation of primary sulphides formed by the zones of primary pyrite and primary chalcopyrite.

o  The supergene zone is formed by a process of rebalancing from hypogenic (hydrothermal) mineralogy to oxidising conditions near the earth's surface. The supergene event has generated three zones; leached, oxides and secondary enrichment.

·    Hypogene sulphide mineralisation forms most of the mineralisation, both in terms of volume and metal content. Hypogene copper sulphides consist predominantly of chalcopyrite.

·    Visual checks were made in 3D, plan and section views and interpretation anomalies were reviewed and modified as appropriate.

·    The geology is well understood due to the long history of exploration and mining in the area and alternate interpretations were therefore not considered.

Dimensions

·    The morphology and extent of the Mineral Resource of the Sierra Gorda deposit is a sub-vertical body with a diameter varying between 1,600m and 2,000m. Currently, the mineralised system has been extended to a depth of 1,800m.

·    The stockpile resource covers an area of over 260ha and is located adjacent to the Catabela pit.

Estimation and modelling techniques

·    Mineralisation domains were developed for each element of economic interest (TCu, Mo and Au). Nine copper domains, four molybdenum domains and seven gold domains were defined based on mineral composition, alteration, lithology and grade cut-off. The domains were validated by exploratory data analysis (EDA).

·    Outlier assessment resulted in capping of high-grade values. Probability plots were generated to identify outliers. Composited data for Mo and Au were capped, while no capping was applied to TCu data.

·    Datamine's Supervisor Software was used for EDA, variography, Quantitative Kriging Neighbourhood Analysis (QKNA) and validation of the resource model. Maptek's Vulcan software was used for resource estimation and reporting.

·    QKNA was used to optimise estimation block size and search neighbourhood (i.e., minimum and maximum samples, number of samples per drill hole, octant definition). The parameters reviewed in the optimisation process were the slope of regression and kriging efficiency. A parent block size of 15m in the X direction by 15m in the Y direction by 16m in the Z direction was used for estimation. No sub-blocking was considered due to the bulk scale of mining.

·    Ordinary kriging was used as the estimation method, with search ellipses defined as the full range of the respective variogram model. Three estimation passes were used. The first pass applies a relatively constrained search neighbourhood intended to capture local grade continuity with higher confidence. Subsequent passes progressively expand the search distances to ensure adequate sample support, particularly in areas of lower data density. Finally, a fourth pass was defined for estimation by considering ten times the original search ellipse to identify potential for future exploration, using current understanding of the behaviour of mineralisation.

·    Kriging efficiency and slope of regression were recorded for each estimation run and for each element, to quantify estimation confidence.

·    The estimate was validated by:

o  visual comparison of the block model with informing data in vertical sections and plans.

o  scatter plots to compare estimated block with the nearest neighbour estimate.

o  swath plots in three orthogonal directions (X, Y and Z) with a defined window to compare estimation with informing composited data (Figure 8).

o  a discrete Gaussian change of support assessment to assess the level of smoothing and potential under- or over-estimation of grade.

o  comparison of the Mineral Resource estimate with a previous estimate which used a different estimation method and reconciliation with production data, indicating a reasonable correlation on a global and local scale.

·    Metallurgical recovery was derived for each block using the metallurgical recovery curve generated from metallurgical test work at different grade intervals (Tables 3 & 4).

·    No deleterious elements were considered for estimation.

·    Correlation between different grade elements was not considered in the estimation process. A correlation study will be completed, and the outcome of the study will be implemented in the next resource update.

·    The grade control model, used as an input to stockpile grades, has been estimated using inverse distance method with a power of two. Search criteria include the surrounding samples to generate a local estimate. The ore tracking system is then used where the parcel of ore moved from pit to stockpile is assigned the grade of the respective block. The volume is assigned to the stockpile material based on the ore tracking system. The stockpiles are classified into four categories, namely low, medium and high grade based on TCu grades, and the transitional material is stored separately.

Moisture

·    Based on experience of neighbouring deposits and preliminary assessment of drill cores, the moisture content appears to be minimal.

·    To date, the laboratory does not record sample weights before or after drying. A moisture study will be completed to verify the moisture content and to validate the dry bulk density assumption.

Cut-off parameters

·    The Mineral Resource is defined by calculating a NSR (US$/tonne) and considering revenue using the agreed price protocol after accounting for metallurgical recovery and deducting mining, processing, transportation and G&A costs. The NSR formula is provided below.

NSR (US$/t) = (Cu Price-Freight Cu Conc.) (US$/lb) * Tcu * RecCu * (2,205 * lb/t)

+ (Mo Price - Freight Mo Conc.) (US$/lb) * Mo * RecMo * (2,205 * lb/t)

+ (Au Price - Freight Au Conc.) (US$/oz) * Au * RecAu / (31.1035gm/oz)

- ((Process + G&A) (US$/t) - (Mining (US$/t))

t - tonnes

Cu Conc. - copper in concentrate

RecCu - metallurgical recovery of copper

Mo Conc. - molybdenum in concentrate

RecMo - metallurgical recovery of molybdenum

Au Conc. - gold in concentrate

RecAu - metallurgical recovery of gold

Mining factors or assumptions

·    A pit optimisation (using the Lerchs-Grossman algorithm) was completed to determine RPEEE for defining the optimised resource boundary (both laterally and vertically) using the parameters in the LOM Plan and JV agreed price protocol. Measured, Indicated and Inferred Resources were all considered as value contributors in the optimisation process.

Metallurgical factors or assumptions

·    Metallurgical recovery was assessed based on current operational performance and test work. The grade recovery curve was then derived from the inputs and is incorporated in the resource model for all paying elements (Tcu, Mo and Au).

Environmental factors or assumptions

·    SGSCM follows a strict guideline of mitigating environmental risks inherent to operations. Some aspects considered in developing the strategic plan include energy and water efficiency, waste reduction, emissions reduction, control of particulate matter and promoting recycling and reuse of materials. There are defined targets which will result in minimising environmental impacts on the operation and within the community.

·    The tailings disposal has appropriate permits in place.

·    The waste dumps are designed to ensure slope stability.

Bulk density

·    The statistical analysis was performed on the density database updated in March 2025, compiled to a sampling support. This database consists of 18,857 records, of which 7,730 records correspond to measurements taken during 2024 and 2025.

·    Historically, density measurements at SGSCM were obtained using the "Dry Density with Paraffin" method. Since 2023, this procedure was replaced using vacuum-sealed plastic bags, allowing for duplicate measurements to estimate the precision of the process. Although this practice is standardised under ASTM D6752 / D6752M: 2018 (Standard Test Method for Bulk Specific Gravity and Density of Compacted Asphalt Mixtures Using Automatic Vacuum Sealing Method), the validation of this approach is documented in internal Technical Report.

Classification

·    The classification methodology is based on the 90:15 criterion originally proposed by Dr. H. Parker in the 1990s and later adopted by several mining companies within the industry (Verly et al., 2014). The method aims to ensure, with 90% confidence, that the estimation error for Measured and Indicated Resources-on an annual and quarterly basis, respectively-remains below 15%. For its implementation, a drill hole spacing analysis (DHSA) was conducted using estimation variance to quantify uncertainty and to define confidence thresholds for Measured and Indicated Resources.

o  Measured resources: Blocks with an equivalent grid of less than 60 meters.

o  Indicated resources: Blocks with an equivalent grid between 60 and 120 meters.

o  Inferred resources: Estimated blocks with an equivalent grid of up to 300 meters.

·    Classification of the stockpile Mineral Resource considers the uncertainty associated with material mining, movement and tracking using equipment fitted with HPGPS (high precision GPS). All stockpile Mineral Resource is classified as Indicated based on the above assessment.

·    The Competent Person is satisfied that the Mineral Resource classification (Figure 9) reflects the geological interpretation and the constraints of the deposit.

Audits or reviews

·    In March 2026, an independent consultant was commissioned by South32 to conduct an audit of the Mineral Resource estimate. The audit did not identify any major shortcomings, and it was concluded that, in general terms, the process of generating the resource model has followed industry standards and the supporting documentation is adequate.

Discussion of relative accuracy/confidence

·    An assessment of confidence was conducted using a conditional simulation study. For each domain at the block dimension (15m X 15m X 16m), 70 realisations were generated for TCu grades and were validated against the sample information. The realisations were re-blocked to reflect quarterly and annual production tonnage. The block dimensions were oriented to be laterally extensive, to mimic the mining technique at Sierra Gorda. A default average density for sulphide material was applied. The 90% confidence interval was compared to the mean grade of the realisations to derive accuracy +/-15%. 

o  annual tonnage assumption - 47Mt

o  quarterly tonnage assumption - 12Mt

·    The Competent Person is satisfied that the accuracy and confidence of Mineral Resource estimation is well established and reasonable for the deposit.